{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import collections\n",
    "\n",
    "import matplotlib.mlab as mlab  \n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "\n",
    "from matplotlib import font_manager as fm\n",
    "from  matplotlib import cm\n",
    "\n",
    "from IPython.display import set_matplotlib_formats\n",
    "set_matplotlib_formats('retina')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "matplotlib.matplotlib_fname()\n",
    "sh1 = pd.read_json('data/SH_ty1.json')\n",
    "sh1_t = sh1.T\n",
    "w = pd.read_json('data/WX_yao.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Shanghan():\n",
    "    def __init__(self):\n",
    "        self.sh1 = pd.read_json('data/SH_ty1.json')\n",
    "        self.wx = {y: sx for sx, yao in w.loc[\"药物\"].iteritems() for y in yao}\n",
    "        pass\n",
    "        \n",
    "        \n",
    "    def bianzheng(self,zheng):#根据证输出对应方剂(简单根据伤寒的对应,而非根据心法)\n",
    "        a = self.sh1.loc['证'].apply(lambda x: set(x['体证']))\n",
    "        print(a[a.apply(lambda x: zheng <= x)].index[0])\n",
    "        \n",
    "                \n",
    "    def find(self,find):#简单查询某一个方剂的信息\n",
    "        self.find = find\n",
    "        print(sh1[self.find])\n",
    "        \n",
    "    def count_all(self,yao):#可以查询每个方剂或药物在整个伤寒里的统计\n",
    "        a = self.sh1.loc['方']\n",
    "        s = a[a.apply(lambda x: yao in x)].count()\n",
    "        print(s)\n",
    "        \n",
    "    \n",
    "    def draw_dir_all(self):#画每一个方剂的方向图\n",
    "        fang = self.sh1.loc['方']\n",
    "        sx = [self.wx.get(y,\"暂不明\") for f in fang for y in f]\n",
    "        sx_len = len(sx)\n",
    "        qq = {y: cnt / sx_len for y, cnt in collections.Counter(sx).items()}\n",
    "        \n",
    "        #----------------下面是画饼图-----------------------------------\n",
    "        \n",
    "        labels = list(qq.keys())\n",
    "        X = list(qq.values())\n",
    "        fig, ax = plt.subplots(figsize=(11,11))\n",
    "        \n",
    "        #fig = plt.figure(1, figsize=(11,11))\n",
    "        \n",
    "        colors = cm.rainbow(np.arange(len(X))/len(X))\n",
    "        patches, texts, autotexts = ax.pie(X, labels=labels, autopct='%1.2f%%',\n",
    "        shadow=False, startangle=170, colors=colors)\n",
    "        \n",
    "        proptease = fm.FontProperties()\n",
    "        proptease.set_size('x-large')\n",
    "        \n",
    "        plt.setp(autotexts, fontproperties=proptease)\n",
    "        plt.setp(texts, fontproperties=proptease)\n",
    "\n",
    "        plt.title(\"伤寒全部方剂五行方向图\", pad = 30)\n",
    "        plt.axis('equal')\n",
    "        plt.show()  \n",
    "        \n",
    "        \n",
    "        \n",
    "    def draw_dir(self,f):\n",
    "        fang = self.sh1.loc['方'][f]\n",
    "        sx = [self.wx.get(y, \"暂不明\") for y in fang]\n",
    "        fang_len = len(fang)\n",
    "        qq = {s: cnt / fang_len for s, cnt in collections.Counter(sx).items()}  #字典解析\n",
    "        \n",
    "        #----------------下面是画饼图-----------------------------------\n",
    "         \n",
    "        labels = list(qq.keys())\n",
    "        X = list(qq.values())\n",
    "        fig, ax = plt.subplots(figsize=(11,11))\n",
    "        \n",
    "        colors = cm.rainbow(np.arange(len(X))/len(X))\n",
    "        patches, texts, autotexts = ax.pie(X, labels=labels, autopct='%1.2f%%',\n",
    "        shadow=False, startangle=170, colors=colors)\n",
    "        \n",
    "        proptease = fm.FontProperties()\n",
    "        proptease.set_size('x-large')\n",
    "        \n",
    "        title = str(f)+'的五行方向图'\n",
    "        \n",
    "        plt.setp(autotexts, fontproperties=proptease)\n",
    "        plt.setp(texts, fontproperties=proptease)\n",
    "        \n",
    "        \n",
    "        plt.title(title, pad = 30)\n",
    "        plt.axis('equal')\n",
    "        plt.show()  \n",
    "        \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'桂枝': '3两', '芍药': '3两', '炙甘草': '2两', '生姜': '3两', '大枣': '12枚'}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sh1.loc['方'][\"桂枝汤\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "br1 = Shanghan()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>桂枝汤</th>\n",
       "      <th>桂枝加葛根汤</th>\n",
       "      <th>桂枝加附子汤</th>\n",
       "      <th>桂枝去芍药汤</th>\n",
       "      <th>桂枝去芍药加附子汤</th>\n",
       "      <th>桂枝麻黄各半汤</th>\n",
       "      <th>桂枝二麻黄一汤</th>\n",
       "      <th>白虎加人参汤</th>\n",
       "      <th>桂枝二越婢一汤</th>\n",
       "      <th>桂枝去桂加茯苓白术汤</th>\n",
       "      <th>...</th>\n",
       "      <th>麻黄升麻汤</th>\n",
       "      <th>干姜黄芩黄连人参汤</th>\n",
       "      <th>白头翁汤</th>\n",
       "      <th>四逆加人参汤</th>\n",
       "      <th>理中丸</th>\n",
       "      <th>通脉四逆加猪胆汤</th>\n",
       "      <th>烧裈散</th>\n",
       "      <th>枳实栀子汤</th>\n",
       "      <th>牡蛎泽泻散</th>\n",
       "      <th>竹叶石膏汤</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>六经</th>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '阳明'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>...</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '少阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '阳明'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '阳明'}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>原文</th>\n",
       "      <td>{'对应证原文': ['吐利止。而身痛不休者。当消息和解其外。宜桂枝汤小和之。'], '方剂...</td>\n",
       "      <td>{'对应证原文': ['太阳病，项背强几几，反汗出恶风者，桂枝加葛根汤主之。', '太阳与阳...</td>\n",
       "      <td>{'对应证原文': ['太阳病，发汗，遂漏不止，其人恶风，小便难，四支微急，难以屈伸者，桂枝...</td>\n",
       "      <td>{'对应证原文': ['太阳病。下之后。脉促。胸满者。桂枝去芍药汤主之。'], '方剂原文'...</td>\n",
       "      <td>{'对应证原文': ['若微寒者。桂枝去芍药加附子汤主之。'], '方剂原文': '桂枝三两...</td>\n",
       "      <td>{'对应证原文': ['面色反有热色者。未欲解也。以其不能得小汗出 。 身必痒。宜桂枝麻黄各...</td>\n",
       "      <td>{'对应证原文': ['服桂枝汤。大汗出。脉洪大者。与桂枝汤如前法。若形似疟。一日再发者。汗...</td>\n",
       "      <td>{'对应证原文': ['若渴欲饮水。口干舌燥者。白虎加人参汤主之。'], '方剂原文': '...</td>\n",
       "      <td>{'对应证原文': ['太阳病。发热恶寒。热多寒少。脉微弱者。此无阳也。不可发汗。宜桂枝二越...</td>\n",
       "      <td>{'对应证原文': ['服桂枝汤。或下之。仍头项强痛。翕翕发热。无汗。心下满微痛。小便不利者...</td>\n",
       "      <td>...</td>\n",
       "      <td>{'对应证原文': ['伤寒。六七日。大下后。寸脉沉而迟。手足厥逆。下部脉不至。喉咽不利。唾...</td>\n",
       "      <td>{'对应证原文': ['伤寒。本自寒下。医复吐下之。寒格。更逆吐下。若食入口即吐。干姜黄芩黄...</td>\n",
       "      <td>{'对应证原文': ['热利下重者。白头翁汤主之。'], '方剂原文': '白头翁二两 黄蘗...</td>\n",
       "      <td>{'对应证原文': ['恶寒。脉微而复利。利止。亡血也。四逆加人参汤主之。'], '方剂原文...</td>\n",
       "      <td>{'对应证原文': ['大病差后。喜唾。久不了了。胸上有寒。当以丸药温之。宜理中丸。'], ...</td>\n",
       "      <td>{'对应证原文': ['吐已下断。汗出而厥。四肢拘急不解。脉微欲绝者。通脉四逆加猪胆汤主之。...</td>\n",
       "      <td>{'对应证原文': ['伤寒阴易之为病。其人身体重。少气。少腹里急。或引阴中拘挛。热上冲胸。...</td>\n",
       "      <td>{'对应证原文': ['大病差后。劳复者。枳实栀子汤主之。'], '方剂原文': '枳实三枚...</td>\n",
       "      <td>{'对应证原文': ['大病差后。从腰以下有水气者。牡蛎泽泻散主之。'], '方剂原文': ...</td>\n",
       "      <td>{'对应证原文': ['伤寒解后。虚羸少气。气逆欲吐。竹叶石膏汤主之。'], '方剂原文':...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>方</th>\n",
       "      <td>{'桂枝': '3两', '芍药': '3两', '炙甘草': '2两', '生姜': '3...</td>\n",
       "      <td>{'葛根': '4两', '桂枝': '3两', '芍药': '2两', '炙甘草': '2...</td>\n",
       "      <td>{'附子': '1两', '桂枝': '3两', '芍药': '3两', '炙甘草': '3...</td>\n",
       "      <td>{'桂枝': '3两', '炙甘草': '2两', '生姜': '3两', '大枣': '1...</td>\n",
       "      <td>{'桂枝': '3两', '炙甘草': '2两', '生姜': '3两', '大枣': '1...</td>\n",
       "      <td>{'桂枝': '1两16铢', '炙甘草': '1两', '生姜': '1两', '大枣':...</td>\n",
       "      <td>{'桂枝': '1两17铢', '炙甘草': '1两6铢', '生姜': '1两6铢', '...</td>\n",
       "      <td>{'知母': '6两', '石膏': '1斤', '粳米': '6合', '炙甘草': '2...</td>\n",
       "      <td>{'桂枝': '1两', '芍药': '1两', '炙甘草': '1两', '麻黄': '1...</td>\n",
       "      <td>{'白术': '3两', '芍药': '3两', '炙甘草': '2两', '茯苓': '3...</td>\n",
       "      <td>...</td>\n",
       "      <td>{'茯苓': '6株', '炙甘草': '6株', '干姜': '6株', '桂枝': '6...</td>\n",
       "      <td>{'人参': '3两', '黄芩': '3两', '干姜': '3两', '黄连': '3两'}</td>\n",
       "      <td>{'白头翁': '2两', '黄蘗': '3两', '黄连': '3两', '秦皮': '3两'}</td>\n",
       "      <td>{'人参': '1两', '附子': '1枚', '炙甘草': '3两', '干姜': '1...</td>\n",
       "      <td>{'人参': '3两', '干姜': '3两', '炙甘草': '3两', '白术': '3两'}</td>\n",
       "      <td>{'附子': '1枚', '炙甘草': '2两', '干姜': '3两', '猪胆汁': '...</td>\n",
       "      <td>{'妇人中裈近隐处之烧灰': '一些'}</td>\n",
       "      <td>{'枳实': '3枚', '栀子': '14个', '豉': '1升'}</td>\n",
       "      <td>{'柴胡': '0.5斤', '黄芩': '3两', '人参': '3两', '半夏': '...</td>\n",
       "      <td>{'竹叶': '2把', '石膏': '1斤', '半夏': '1升', '麦门冬': '1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>证</th>\n",
       "      <td>{'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...</td>\n",
       "      <td>{'体证': ['肌肉酸痛', '怕风'], '脉证': ['无']}</td>\n",
       "      <td>{'体证': ['大量出汗不止', '怕风', '小便难', '四肢难以屈伸'], '脉证'...</td>\n",
       "      <td>{'体证': ['大便后胸胀'], '脉证': ['急促']}</td>\n",
       "      <td>{'体证': ['口苦', '轻微寒冷'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['身痒'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['暂无'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['暂无'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['发热怕冷', '热多寒少'], '脉证': ['微弱']}</td>\n",
       "      <td>{'体证': ['严重头痛', '发热无汗', '心下满', '小便不多', '身体微痛']...</td>\n",
       "      <td>...</td>\n",
       "      <td>{'体证': ['暂无'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['暂无'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...</td>\n",
       "      <td>{'体证': ['喜睡眠', '胸满胁痛'], '脉证': ['脉细']}</td>\n",
       "      <td>{'体证': ['消渴'], '脉证': ['脉沉紧']}</td>\n",
       "      <td>{'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...</td>\n",
       "      <td>{'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...</td>\n",
       "      <td>{'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...</td>\n",
       "      <td>{'体证': ['喜睡眠', '胸满胁痛'], '脉证': ['脉细']}</td>\n",
       "      <td>{'体证': ['消渴'], '脉证': ['脉沉紧']}</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4 rows × 111 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  桂枝汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['吐利止。而身痛不休者。当消息和解其外。宜桂枝汤小和之。'], '方剂...   \n",
       "方   {'桂枝': '3两', '芍药': '3两', '炙甘草': '2两', '生姜': '3...   \n",
       "证   {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...   \n",
       "\n",
       "                                               桂枝加葛根汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['太阳病，项背强几几，反汗出恶风者，桂枝加葛根汤主之。', '太阳与阳...   \n",
       "方   {'葛根': '4两', '桂枝': '3两', '芍药': '2两', '炙甘草': '2...   \n",
       "证                 {'体证': ['肌肉酸痛', '怕风'], '脉证': ['无']}   \n",
       "\n",
       "                                               桂枝加附子汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['太阳病，发汗，遂漏不止，其人恶风，小便难，四支微急，难以屈伸者，桂枝...   \n",
       "方   {'附子': '1两', '桂枝': '3两', '芍药': '3两', '炙甘草': '3...   \n",
       "证   {'体证': ['大量出汗不止', '怕风', '小便难', '四肢难以屈伸'], '脉证'...   \n",
       "\n",
       "                                               桂枝去芍药汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['太阳病。下之后。脉促。胸满者。桂枝去芍药汤主之。'], '方剂原文'...   \n",
       "方   {'桂枝': '3两', '炙甘草': '2两', '生姜': '3两', '大枣': '1...   \n",
       "证                     {'体证': ['大便后胸胀'], '脉证': ['急促']}   \n",
       "\n",
       "                                            桂枝去芍药加附子汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['若微寒者。桂枝去芍药加附子汤主之。'], '方剂原文': '桂枝三两...   \n",
       "方   {'桂枝': '3两', '炙甘草': '2两', '生姜': '3两', '大枣': '1...   \n",
       "证                {'体证': ['口苦', '轻微寒冷'], '脉证': ['暂无']}   \n",
       "\n",
       "                                              桂枝麻黄各半汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['面色反有热色者。未欲解也。以其不能得小汗出 。 身必痒。宜桂枝麻黄各...   \n",
       "方   {'桂枝': '1两16铢', '炙甘草': '1两', '生姜': '1两', '大枣':...   \n",
       "证                        {'体证': ['身痒'], '脉证': ['暂无']}   \n",
       "\n",
       "                                              桂枝二麻黄一汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['服桂枝汤。大汗出。脉洪大者。与桂枝汤如前法。若形似疟。一日再发者。汗...   \n",
       "方   {'桂枝': '1两17铢', '炙甘草': '1两6铢', '生姜': '1两6铢', '...   \n",
       "证                        {'体证': ['暂无'], '脉证': ['暂无']}   \n",
       "\n",
       "                                               白虎加人参汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '阳明'}   \n",
       "原文  {'对应证原文': ['若渴欲饮水。口干舌燥者。白虎加人参汤主之。'], '方剂原文': '...   \n",
       "方   {'知母': '6两', '石膏': '1斤', '粳米': '6合', '炙甘草': '2...   \n",
       "证                        {'体证': ['暂无'], '脉证': ['暂无']}   \n",
       "\n",
       "                                              桂枝二越婢一汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['太阳病。发热恶寒。热多寒少。脉微弱者。此无阳也。不可发汗。宜桂枝二越...   \n",
       "方   {'桂枝': '1两', '芍药': '1两', '炙甘草': '1两', '麻黄': '1...   \n",
       "证              {'体证': ['发热怕冷', '热多寒少'], '脉证': ['微弱']}   \n",
       "\n",
       "                                           桂枝去桂加茯苓白术汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['服桂枝汤。或下之。仍头项强痛。翕翕发热。无汗。心下满微痛。小便不利者...   \n",
       "方   {'白术': '3两', '芍药': '3两', '炙甘草': '2两', '茯苓': '3...   \n",
       "证   {'体证': ['严重头痛', '发热无汗', '心下满', '小便不多', '身体微痛']...   \n",
       "\n",
       "                          ...                          \\\n",
       "六经                        ...                           \n",
       "原文                        ...                           \n",
       "方                         ...                           \n",
       "证                         ...                           \n",
       "\n",
       "                                                麻黄升麻汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['伤寒。六七日。大下后。寸脉沉而迟。手足厥逆。下部脉不至。喉咽不利。唾...   \n",
       "方   {'茯苓': '6株', '炙甘草': '6株', '干姜': '6株', '桂枝': '6...   \n",
       "证                        {'体证': ['暂无'], '脉证': ['暂无']}   \n",
       "\n",
       "                                            干姜黄芩黄连人参汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['伤寒。本自寒下。医复吐下之。寒格。更逆吐下。若食入口即吐。干姜黄芩黄...   \n",
       "方    {'人参': '3两', '黄芩': '3两', '干姜': '3两', '黄连': '3两'}   \n",
       "证                        {'体证': ['暂无'], '脉证': ['暂无']}   \n",
       "\n",
       "                                                 白头翁汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '少阴'}   \n",
       "原文  {'对应证原文': ['热利下重者。白头翁汤主之。'], '方剂原文': '白头翁二两 黄蘗...   \n",
       "方   {'白头翁': '2两', '黄蘗': '3两', '黄连': '3两', '秦皮': '3两'}   \n",
       "证   {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...   \n",
       "\n",
       "                                               四逆加人参汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['恶寒。脉微而复利。利止。亡血也。四逆加人参汤主之。'], '方剂原文...   \n",
       "方   {'人参': '1两', '附子': '1枚', '炙甘草': '3两', '干姜': '1...   \n",
       "证               {'体证': ['喜睡眠', '胸满胁痛'], '脉证': ['脉细']}   \n",
       "\n",
       "                                                  理中丸  \\\n",
       "六经                            {'阴阳': '阳', '三经': '阳明'}   \n",
       "原文  {'对应证原文': ['大病差后。喜唾。久不了了。胸上有寒。当以丸药温之。宜理中丸。'], ...   \n",
       "方   {'人参': '3两', '干姜': '3两', '炙甘草': '3两', '白术': '3两'}   \n",
       "证                       {'体证': ['消渴'], '脉证': ['脉沉紧']}   \n",
       "\n",
       "                                             通脉四逆加猪胆汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['吐已下断。汗出而厥。四肢拘急不解。脉微欲绝者。通脉四逆加猪胆汤主之。...   \n",
       "方   {'附子': '1枚', '炙甘草': '2两', '干姜': '3两', '猪胆汁': '...   \n",
       "证   {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...   \n",
       "\n",
       "                                                  烧裈散  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['伤寒阴易之为病。其人身体重。少气。少腹里急。或引阴中拘挛。热上冲胸。...   \n",
       "方                                {'妇人中裈近隐处之烧灰': '一些'}   \n",
       "证   {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...   \n",
       "\n",
       "                                                枳实栀子汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['大病差后。劳复者。枳实栀子汤主之。'], '方剂原文': '枳实三枚...   \n",
       "方                {'枳实': '3枚', '栀子': '14个', '豉': '1升'}   \n",
       "证   {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...   \n",
       "\n",
       "                                                牡蛎泽泻散  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['大病差后。从腰以下有水气者。牡蛎泽泻散主之。'], '方剂原文': ...   \n",
       "方   {'柴胡': '0.5斤', '黄芩': '3两', '人参': '3两', '半夏': '...   \n",
       "证               {'体证': ['喜睡眠', '胸满胁痛'], '脉证': ['脉细']}   \n",
       "\n",
       "                                                竹叶石膏汤  \n",
       "六经                            {'阴阳': '阳', '三经': '阳明'}  \n",
       "原文  {'对应证原文': ['伤寒解后。虚羸少气。气逆欲吐。竹叶石膏汤主之。'], '方剂原文':...  \n",
       "方   {'竹叶': '2把', '石膏': '1斤', '半夏': '1升', '麦门冬': '1...  \n",
       "证                       {'体证': ['消渴'], '脉证': ['脉沉紧']}  \n",
       "\n",
       "[4 rows x 111 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sh1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "a1 = sh1.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'<=' not supported between instances of 'list' and 'set'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-8-d06ba4cfbf3a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mbr1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbianzheng\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'怕风'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m<ipython-input-3-630bfa257f00>\u001b[0m in \u001b[0;36mbianzheng\u001b[0;34m(self, zheng)\u001b[0m\n\u001b[1;32m      8\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mbianzheng\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mzheng\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;31m#根据证输出对应方剂(简单根据伤寒的对应,而非根据心法)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m         \u001b[0ma\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msh1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'证'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'体证'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m         \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mzheng\u001b[0m \u001b[0;34m<=\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     11\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda3/lib/python3.7/site-packages/pandas/core/series.py\u001b[0m in \u001b[0;36mapply\u001b[0;34m(self, func, convert_dtype, args, **kwds)\u001b[0m\n\u001b[1;32m   3192\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3193\u001b[0m                 \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobject\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3194\u001b[0;31m                 \u001b[0mmapped\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmap_infer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconvert\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mconvert_dtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3195\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3196\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmapped\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmapped\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mSeries\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/src/inference.pyx\u001b[0m in \u001b[0;36mpandas._libs.lib.map_infer\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32m<ipython-input-3-630bfa257f00>\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m(x)\u001b[0m\n\u001b[1;32m      8\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mbianzheng\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mzheng\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;31m#根据证输出对应方剂(简单根据伤寒的对应,而非根据心法)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m         \u001b[0ma\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msh1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'证'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'体证'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m         \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mzheng\u001b[0m \u001b[0;34m<=\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     11\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: '<=' not supported between instances of 'list' and 'set'"
     ]
    }
   ],
   "source": [
    "br1.bianzheng(['怕风'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "a2 = list(a1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(a2)#一共有111个独特的方子,但需要计算重复的"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'a2' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-9-2878578d440a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ma2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcount\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"桂枝汤\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'a2' is not defined"
     ]
    }
   ],
   "source": [
    "a2.count(\"桂枝汤\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sh1.columns.contains(\"桂枝汤\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7\n"
     ]
    }
   ],
   "source": [
    "br1.count_all(\"柴胡\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['六经', '原文', '方', '证'], dtype='object')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sh1.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x792 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "br1.draw_dir('小柴胡汤')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x792 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "br1.draw_dir_all()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x792 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "br1.draw_dir('桂枝麻黄各半汤')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x792 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "br1.draw_dir('四逆汤')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "桂枝去芍药加附子汤\n"
     ]
    }
   ],
   "source": [
    "br1.bianzheng({'口苦'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "桂枝汤\n"
     ]
    }
   ],
   "source": [
    "br1.bianzheng({'怕风'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x792 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "br1.draw_dir('桂枝加附子汤')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "65\n"
     ]
    }
   ],
   "source": [
    "br1.count_all('炙甘草')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>桂枝汤</th>\n",
       "      <th>桂枝加葛根汤</th>\n",
       "      <th>桂枝加附子汤</th>\n",
       "      <th>桂枝去芍药汤</th>\n",
       "      <th>桂枝去芍药加附子汤</th>\n",
       "      <th>桂枝麻黄各半汤</th>\n",
       "      <th>桂枝二麻黄一汤</th>\n",
       "      <th>白虎加人参汤</th>\n",
       "      <th>桂枝二越婢一汤</th>\n",
       "      <th>桂枝去桂加茯苓白术汤</th>\n",
       "      <th>...</th>\n",
       "      <th>麻黄升麻汤</th>\n",
       "      <th>干姜黄芩黄连人参汤</th>\n",
       "      <th>白头翁汤</th>\n",
       "      <th>四逆加人参汤</th>\n",
       "      <th>理中丸</th>\n",
       "      <th>通脉四逆加猪胆汤</th>\n",
       "      <th>烧裈散</th>\n",
       "      <th>枳实栀子汤</th>\n",
       "      <th>牡蛎泽泻散</th>\n",
       "      <th>竹叶石膏汤</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>六经</th>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '阳明'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>...</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '少阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '阳明'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '阳明'}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>原文</th>\n",
       "      <td>{'对应证原文': ['吐利止。而身痛不休者。当消息和解其外。宜桂枝汤小和之。'], '方剂...</td>\n",
       "      <td>{'对应证原文': ['太阳病，项背强几几，反汗出恶风者，桂枝加葛根汤主之。', '太阳与阳...</td>\n",
       "      <td>{'对应证原文': ['太阳病，发汗，遂漏不止，其人恶风，小便难，四支微急，难以屈伸者，桂枝...</td>\n",
       "      <td>{'对应证原文': ['太阳病。下之后。脉促。胸满者。桂枝去芍药汤主之。'], '方剂原文'...</td>\n",
       "      <td>{'对应证原文': ['若微寒者。桂枝去芍药加附子汤主之。'], '方剂原文': '桂枝三两...</td>\n",
       "      <td>{'对应证原文': ['面色反有热色者。未欲解也。以其不能得小汗出 。 身必痒。宜桂枝麻黄各...</td>\n",
       "      <td>{'对应证原文': ['服桂枝汤。大汗出。脉洪大者。与桂枝汤如前法。若形似疟。一日再发者。汗...</td>\n",
       "      <td>{'对应证原文': ['若渴欲饮水。口干舌燥者。白虎加人参汤主之。'], '方剂原文': '...</td>\n",
       "      <td>{'对应证原文': ['太阳病。发热恶寒。热多寒少。脉微弱者。此无阳也。不可发汗。宜桂枝二越...</td>\n",
       "      <td>{'对应证原文': ['服桂枝汤。或下之。仍头项强痛。翕翕发热。无汗。心下满微痛。小便不利者...</td>\n",
       "      <td>...</td>\n",
       "      <td>{'对应证原文': ['伤寒。六七日。大下后。寸脉沉而迟。手足厥逆。下部脉不至。喉咽不利。唾...</td>\n",
       "      <td>{'对应证原文': ['伤寒。本自寒下。医复吐下之。寒格。更逆吐下。若食入口即吐。干姜黄芩黄...</td>\n",
       "      <td>{'对应证原文': ['热利下重者。白头翁汤主之。'], '方剂原文': '白头翁二两 黄蘗...</td>\n",
       "      <td>{'对应证原文': ['恶寒。脉微而复利。利止。亡血也。四逆加人参汤主之。'], '方剂原文...</td>\n",
       "      <td>{'对应证原文': ['大病差后。喜唾。久不了了。胸上有寒。当以丸药温之。宜理中丸。'], ...</td>\n",
       "      <td>{'对应证原文': ['吐已下断。汗出而厥。四肢拘急不解。脉微欲绝者。通脉四逆加猪胆汤主之。...</td>\n",
       "      <td>{'对应证原文': ['伤寒阴易之为病。其人身体重。少气。少腹里急。或引阴中拘挛。热上冲胸。...</td>\n",
       "      <td>{'对应证原文': ['大病差后。劳复者。枳实栀子汤主之。'], '方剂原文': '枳实三枚...</td>\n",
       "      <td>{'对应证原文': ['大病差后。从腰以下有水气者。牡蛎泽泻散主之。'], '方剂原文': ...</td>\n",
       "      <td>{'对应证原文': ['伤寒解后。虚羸少气。气逆欲吐。竹叶石膏汤主之。'], '方剂原文':...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>方</th>\n",
       "      <td>{'桂枝': '3两', '芍药': '3两', '炙甘草': '2两', '生姜': '3...</td>\n",
       "      <td>{'葛根': '4两', '桂枝': '3两', '芍药': '2两', '炙甘草': '2...</td>\n",
       "      <td>{'附子': '1两', '桂枝': '3两', '芍药': '3两', '炙甘草': '3...</td>\n",
       "      <td>{'桂枝': '3两', '炙甘草': '2两', '生姜': '3两', '大枣': '1...</td>\n",
       "      <td>{'桂枝': '3两', '炙甘草': '2两', '生姜': '3两', '大枣': '1...</td>\n",
       "      <td>{'桂枝': '1两16铢', '炙甘草': '1两', '生姜': '1两', '大枣':...</td>\n",
       "      <td>{'桂枝': '1两17铢', '炙甘草': '1两6铢', '生姜': '1两6铢', '...</td>\n",
       "      <td>{'知母': '6两', '石膏': '1斤', '粳米': '6合', '炙甘草': '2...</td>\n",
       "      <td>{'桂枝': '1两', '芍药': '1两', '炙甘草': '1两', '麻黄': '1...</td>\n",
       "      <td>{'白术': '3两', '芍药': '3两', '炙甘草': '2两', '茯苓': '3...</td>\n",
       "      <td>...</td>\n",
       "      <td>{'茯苓': '6株', '炙甘草': '6株', '干姜': '6株', '桂枝': '6...</td>\n",
       "      <td>{'人参': '3两', '黄芩': '3两', '干姜': '3两', '黄连': '3两'}</td>\n",
       "      <td>{'白头翁': '2两', '黄蘗': '3两', '黄连': '3两', '秦皮': '3两'}</td>\n",
       "      <td>{'人参': '1两', '附子': '1枚', '炙甘草': '3两', '干姜': '1...</td>\n",
       "      <td>{'人参': '3两', '干姜': '3两', '炙甘草': '3两', '白术': '3两'}</td>\n",
       "      <td>{'附子': '1枚', '炙甘草': '2两', '干姜': '3两', '猪胆汁': '...</td>\n",
       "      <td>{'妇人中裈近隐处之烧灰': '一些'}</td>\n",
       "      <td>{'枳实': '3枚', '栀子': '14个', '豉': '1升'}</td>\n",
       "      <td>{'柴胡': '0.5斤', '黄芩': '3两', '人参': '3两', '半夏': '...</td>\n",
       "      <td>{'竹叶': '2把', '石膏': '1斤', '半夏': '1升', '麦门冬': '1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>证</th>\n",
       "      <td>{'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...</td>\n",
       "      <td>{'体证': ['肌肉酸痛', '怕风'], '脉证': ['无']}</td>\n",
       "      <td>{'体证': ['大量出汗不止', '怕风', '小便难', '四肢难以屈伸'], '脉证'...</td>\n",
       "      <td>{'体证': ['大便后胸胀'], '脉证': ['急促']}</td>\n",
       "      <td>{'体证': ['口苦', '轻微寒冷'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['身痒'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['暂无'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['暂无'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['发热怕冷', '热多寒少'], '脉证': ['微弱']}</td>\n",
       "      <td>{'体证': ['严重头痛', '发热无汗', '心下满', '小便不多', '身体微痛']...</td>\n",
       "      <td>...</td>\n",
       "      <td>{'体证': ['暂无'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['暂无'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...</td>\n",
       "      <td>{'体证': ['喜睡眠', '胸满胁痛'], '脉证': ['脉细']}</td>\n",
       "      <td>{'体证': ['消渴'], '脉证': ['脉沉紧']}</td>\n",
       "      <td>{'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...</td>\n",
       "      <td>{'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...</td>\n",
       "      <td>{'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...</td>\n",
       "      <td>{'体证': ['喜睡眠', '胸满胁痛'], '脉证': ['脉细']}</td>\n",
       "      <td>{'体证': ['消渴'], '脉证': ['脉沉紧']}</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4 rows × 111 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  桂枝汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['吐利止。而身痛不休者。当消息和解其外。宜桂枝汤小和之。'], '方剂...   \n",
       "方   {'桂枝': '3两', '芍药': '3两', '炙甘草': '2两', '生姜': '3...   \n",
       "证   {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...   \n",
       "\n",
       "                                               桂枝加葛根汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['太阳病，项背强几几，反汗出恶风者，桂枝加葛根汤主之。', '太阳与阳...   \n",
       "方   {'葛根': '4两', '桂枝': '3两', '芍药': '2两', '炙甘草': '2...   \n",
       "证                 {'体证': ['肌肉酸痛', '怕风'], '脉证': ['无']}   \n",
       "\n",
       "                                               桂枝加附子汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['太阳病，发汗，遂漏不止，其人恶风，小便难，四支微急，难以屈伸者，桂枝...   \n",
       "方   {'附子': '1两', '桂枝': '3两', '芍药': '3两', '炙甘草': '3...   \n",
       "证   {'体证': ['大量出汗不止', '怕风', '小便难', '四肢难以屈伸'], '脉证'...   \n",
       "\n",
       "                                               桂枝去芍药汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['太阳病。下之后。脉促。胸满者。桂枝去芍药汤主之。'], '方剂原文'...   \n",
       "方   {'桂枝': '3两', '炙甘草': '2两', '生姜': '3两', '大枣': '1...   \n",
       "证                     {'体证': ['大便后胸胀'], '脉证': ['急促']}   \n",
       "\n",
       "                                            桂枝去芍药加附子汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['若微寒者。桂枝去芍药加附子汤主之。'], '方剂原文': '桂枝三两...   \n",
       "方   {'桂枝': '3两', '炙甘草': '2两', '生姜': '3两', '大枣': '1...   \n",
       "证                {'体证': ['口苦', '轻微寒冷'], '脉证': ['暂无']}   \n",
       "\n",
       "                                              桂枝麻黄各半汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['面色反有热色者。未欲解也。以其不能得小汗出 。 身必痒。宜桂枝麻黄各...   \n",
       "方   {'桂枝': '1两16铢', '炙甘草': '1两', '生姜': '1两', '大枣':...   \n",
       "证                        {'体证': ['身痒'], '脉证': ['暂无']}   \n",
       "\n",
       "                                              桂枝二麻黄一汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['服桂枝汤。大汗出。脉洪大者。与桂枝汤如前法。若形似疟。一日再发者。汗...   \n",
       "方   {'桂枝': '1两17铢', '炙甘草': '1两6铢', '生姜': '1两6铢', '...   \n",
       "证                        {'体证': ['暂无'], '脉证': ['暂无']}   \n",
       "\n",
       "                                               白虎加人参汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '阳明'}   \n",
       "原文  {'对应证原文': ['若渴欲饮水。口干舌燥者。白虎加人参汤主之。'], '方剂原文': '...   \n",
       "方   {'知母': '6两', '石膏': '1斤', '粳米': '6合', '炙甘草': '2...   \n",
       "证                        {'体证': ['暂无'], '脉证': ['暂无']}   \n",
       "\n",
       "                                              桂枝二越婢一汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['太阳病。发热恶寒。热多寒少。脉微弱者。此无阳也。不可发汗。宜桂枝二越...   \n",
       "方   {'桂枝': '1两', '芍药': '1两', '炙甘草': '1两', '麻黄': '1...   \n",
       "证              {'体证': ['发热怕冷', '热多寒少'], '脉证': ['微弱']}   \n",
       "\n",
       "                                           桂枝去桂加茯苓白术汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['服桂枝汤。或下之。仍头项强痛。翕翕发热。无汗。心下满微痛。小便不利者...   \n",
       "方   {'白术': '3两', '芍药': '3两', '炙甘草': '2两', '茯苓': '3...   \n",
       "证   {'体证': ['严重头痛', '发热无汗', '心下满', '小便不多', '身体微痛']...   \n",
       "\n",
       "                          ...                          \\\n",
       "六经                        ...                           \n",
       "原文                        ...                           \n",
       "方                         ...                           \n",
       "证                         ...                           \n",
       "\n",
       "                                                麻黄升麻汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['伤寒。六七日。大下后。寸脉沉而迟。手足厥逆。下部脉不至。喉咽不利。唾...   \n",
       "方   {'茯苓': '6株', '炙甘草': '6株', '干姜': '6株', '桂枝': '6...   \n",
       "证                        {'体证': ['暂无'], '脉证': ['暂无']}   \n",
       "\n",
       "                                            干姜黄芩黄连人参汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['伤寒。本自寒下。医复吐下之。寒格。更逆吐下。若食入口即吐。干姜黄芩黄...   \n",
       "方    {'人参': '3两', '黄芩': '3两', '干姜': '3两', '黄连': '3两'}   \n",
       "证                        {'体证': ['暂无'], '脉证': ['暂无']}   \n",
       "\n",
       "                                                 白头翁汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '少阴'}   \n",
       "原文  {'对应证原文': ['热利下重者。白头翁汤主之。'], '方剂原文': '白头翁二两 黄蘗...   \n",
       "方   {'白头翁': '2两', '黄蘗': '3两', '黄连': '3两', '秦皮': '3两'}   \n",
       "证   {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...   \n",
       "\n",
       "                                               四逆加人参汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['恶寒。脉微而复利。利止。亡血也。四逆加人参汤主之。'], '方剂原文...   \n",
       "方   {'人参': '1两', '附子': '1枚', '炙甘草': '3两', '干姜': '1...   \n",
       "证               {'体证': ['喜睡眠', '胸满胁痛'], '脉证': ['脉细']}   \n",
       "\n",
       "                                                  理中丸  \\\n",
       "六经                            {'阴阳': '阳', '三经': '阳明'}   \n",
       "原文  {'对应证原文': ['大病差后。喜唾。久不了了。胸上有寒。当以丸药温之。宜理中丸。'], ...   \n",
       "方   {'人参': '3两', '干姜': '3两', '炙甘草': '3两', '白术': '3两'}   \n",
       "证                       {'体证': ['消渴'], '脉证': ['脉沉紧']}   \n",
       "\n",
       "                                             通脉四逆加猪胆汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['吐已下断。汗出而厥。四肢拘急不解。脉微欲绝者。通脉四逆加猪胆汤主之。...   \n",
       "方   {'附子': '1枚', '炙甘草': '2两', '干姜': '3两', '猪胆汁': '...   \n",
       "证   {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...   \n",
       "\n",
       "                                                  烧裈散  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['伤寒阴易之为病。其人身体重。少气。少腹里急。或引阴中拘挛。热上冲胸。...   \n",
       "方                                {'妇人中裈近隐处之烧灰': '一些'}   \n",
       "证   {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...   \n",
       "\n",
       "                                                枳实栀子汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['大病差后。劳复者。枳实栀子汤主之。'], '方剂原文': '枳实三枚...   \n",
       "方                {'枳实': '3枚', '栀子': '14个', '豉': '1升'}   \n",
       "证   {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...   \n",
       "\n",
       "                                                牡蛎泽泻散  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['大病差后。从腰以下有水气者。牡蛎泽泻散主之。'], '方剂原文': ...   \n",
       "方   {'柴胡': '0.5斤', '黄芩': '3两', '人参': '3两', '半夏': '...   \n",
       "证               {'体证': ['喜睡眠', '胸满胁痛'], '脉证': ['脉细']}   \n",
       "\n",
       "                                                竹叶石膏汤  \n",
       "六经                            {'阴阳': '阳', '三经': '阳明'}  \n",
       "原文  {'对应证原文': ['伤寒解后。虚羸少气。气逆欲吐。竹叶石膏汤主之。'], '方剂原文':...  \n",
       "方   {'竹叶': '2把', '石膏': '1斤', '半夏': '1升', '麦门冬': '1...  \n",
       "证                       {'体证': ['消渴'], '脉证': ['脉沉紧']}  \n",
       "\n",
       "[4 rows x 111 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sh1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "桂枝汤                         {怕风, 鼻涕, 发热, 怕冷, 出汗, 头痛, 干呕}\n",
       "桂枝加葛根汤                                        {怕风, 肌肉酸痛}\n",
       "桂枝加附子汤                         {小便难, 四肢难以屈伸, 怕风, 大量出汗不止}\n",
       "桂枝去芍药汤                                           {大便后胸胀}\n",
       "桂枝去芍药加附子汤                                     {口苦, 轻微寒冷}\n",
       "桂枝麻黄各半汤                                             {身痒}\n",
       "桂枝二麻黄一汤                                             {暂无}\n",
       "白虎加人参汤                                              {暂无}\n",
       "桂枝二越婢一汤                                     {发热怕冷, 热多寒少}\n",
       "桂枝去桂加茯苓白术汤                 {严重头痛, 心下满, 发热无汗, 身体微痛, 小便不多}\n",
       "甘草干姜汤                                       {烦躁, 咽喉干, 吐}\n",
       "芍药甘草汤                                               {暂无}\n",
       "调胃承气汤                                               {暂无}\n",
       "四逆汤                  {长期抑郁, 没有精神, 自感体虚, 长期焦虑, 四肢冷, 总想睡觉}\n",
       "葛根汤                                         {背痛, 怕风, 无汗}\n",
       "葛根加半夏汤                                          {无小便而呕吐}\n",
       "葛根黄芩黄连汤                                     {喘而出汗, 小便不止}\n",
       "麻黄汤                      {腰痛, 怕风, 身疼, 骨节痛, 发热, 头痛, 无汗而喘}\n",
       "小柴胡汤                                         {胸满胁痛, 喜睡眠}\n",
       "大青龙汤                               {怕冷, 不出汗而烦躁, 发热, 身体痛}\n",
       "小青龙汤                               {怕冷, 不出汗而烦躁, 发热, 身体痛}\n",
       "桂枝加厚朴杏子汤                                            {微喘}\n",
       "干姜附子汤                              {怕冷, 不出汗而烦躁, 发热, 身体痛}\n",
       "桂枝加芍药生姜各一两人参三两新加汤                  {怕冷, 不出汗而烦躁, 发热, 身体痛}\n",
       "麻黄杏仁甘草石膏汤                          {怕冷, 不出汗而烦躁, 发热, 身体痛}\n",
       "桂枝甘草汤                                   {发汗过多, 手心冒汗, 心悸}\n",
       "茯苓桂枝甘草大枣汤                                    {发汗, 肚脐下悸动}\n",
       "茯苓桂枝白术甘草汤                                {起身头眩晕, 心口下气上冲}\n",
       "芍药甘草附子汤                                          {发汗而怕冷}\n",
       "茯苓四逆汤                                            {发汗而怕冷}\n",
       "                                    ...                 \n",
       "麻黄连轺赤小豆汤                                            {消渴}\n",
       "桂枝加芍药汤                      {怕风, 鼻涕, 发热, 怕冷, 出汗, 头痛, 干呕}\n",
       "桂枝加大黄汤                      {怕风, 鼻涕, 发热, 怕冷, 出汗, 头痛, 干呕}\n",
       "麻黄细辛附子汤                     {怕风, 鼻涕, 发热, 怕冷, 出汗, 头痛, 干呕}\n",
       "麻黄附子甘草汤                     {怕风, 鼻涕, 发热, 怕冷, 出汗, 头痛, 干呕}\n",
       "黄连阿胶汤                       {怕风, 鼻涕, 发热, 怕冷, 出汗, 头痛, 干呕}\n",
       "附子汤                         {怕风, 鼻涕, 发热, 怕冷, 出汗, 头痛, 干呕}\n",
       "桃花汤                         {怕风, 鼻涕, 发热, 怕冷, 出汗, 头痛, 干呕}\n",
       "猪肤汤                         {怕风, 鼻涕, 发热, 怕冷, 出汗, 头痛, 干呕}\n",
       "甘草汤                         {怕风, 鼻涕, 发热, 怕冷, 出汗, 头痛, 干呕}\n",
       "桔梗汤                         {怕风, 鼻涕, 发热, 怕冷, 出汗, 头痛, 干呕}\n",
       "苦酒汤                         {怕风, 鼻涕, 发热, 怕冷, 出汗, 头痛, 干呕}\n",
       "半夏散及汤                       {怕风, 鼻涕, 发热, 怕冷, 出汗, 头痛, 干呕}\n",
       "白通汤                         {怕风, 鼻涕, 发热, 怕冷, 出汗, 头痛, 干呕}\n",
       "白通加猪胆汁汤                     {怕风, 鼻涕, 发热, 怕冷, 出汗, 头痛, 干呕}\n",
       "通脉四逆汤                {长期抑郁, 没有精神, 自感体虚, 长期焦虑, 四肢冷, 总想睡觉}\n",
       "四逆散                  {长期抑郁, 没有精神, 自感体虚, 长期焦虑, 四肢冷, 总想睡觉}\n",
       "乌梅丸                  {长期抑郁, 没有精神, 自感体虚, 长期焦虑, 四肢冷, 总想睡觉}\n",
       "当归四逆汤                {长期抑郁, 没有精神, 自感体虚, 长期焦虑, 四肢冷, 总想睡觉}\n",
       "当归四逆加吴茱萸生姜汤          {长期抑郁, 没有精神, 自感体虚, 长期焦虑, 四肢冷, 总想睡觉}\n",
       "麻黄升麻汤                                               {暂无}\n",
       "干姜黄芩黄连人参汤                                           {暂无}\n",
       "白头翁汤                 {长期抑郁, 没有精神, 自感体虚, 长期焦虑, 四肢冷, 总想睡觉}\n",
       "四逆加人参汤                                       {胸满胁痛, 喜睡眠}\n",
       "理中丸                                                 {消渴}\n",
       "通脉四逆加猪胆汤             {长期抑郁, 没有精神, 自感体虚, 长期焦虑, 四肢冷, 总想睡觉}\n",
       "烧裈散                  {长期抑郁, 没有精神, 自感体虚, 长期焦虑, 四肢冷, 总想睡觉}\n",
       "枳实栀子汤                {长期抑郁, 没有精神, 自感体虚, 长期焦虑, 四肢冷, 总想睡觉}\n",
       "牡蛎泽泻散                                        {胸满胁痛, 喜睡眠}\n",
       "竹叶石膏汤                                               {消渴}\n",
       "Name: 证, Length: 111, dtype: object"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sh1.loc['证'].apply(lambda x: set(x['体证']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "桂枝汤                  {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...\n",
       "桂枝加葛根汤                             {'体证': ['肌肉酸痛', '怕风'], '脉证': ['无']}\n",
       "桂枝加附子汤               {'体证': ['大量出汗不止', '怕风', '小便难', '四肢难以屈伸'], '脉证'...\n",
       "桂枝去芍药汤                                 {'体证': ['大便后胸胀'], '脉证': ['急促']}\n",
       "桂枝去芍药加附子汤                         {'体证': ['口苦', '轻微寒冷'], '脉证': ['暂无']}\n",
       "桂枝麻黄各半汤                                   {'体证': ['身痒'], '脉证': ['暂无']}\n",
       "桂枝二麻黄一汤                                   {'体证': ['暂无'], '脉证': ['暂无']}\n",
       "白虎加人参汤                                    {'体证': ['暂无'], '脉证': ['暂无']}\n",
       "桂枝二越婢一汤                         {'体证': ['发热怕冷', '热多寒少'], '脉证': ['微弱']}\n",
       "桂枝去桂加茯苓白术汤           {'体证': ['严重头痛', '发热无汗', '心下满', '小便不多', '身体微痛']...\n",
       "甘草干姜汤                         {'体证': ['咽喉干', '烦躁', '吐'], '脉证': ['暂无']}\n",
       "芍药甘草汤                                     {'体证': ['暂无'], '脉证': ['暂无']}\n",
       "调胃承气汤                                    {'体证': ['暂无'], '脉证': ['脉沉紧']}\n",
       "四逆汤                  {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...\n",
       "葛根汤                           {'体证': ['无汗', '背痛', '怕风'], '脉证': ['暂无']}\n",
       "葛根加半夏汤                                {'体证': ['无小便而呕吐'], '脉证': ['暂无']}\n",
       "葛根黄芩黄连汤                         {'体证': ['小便不止', '喘而出汗'], '脉证': ['脉促']}\n",
       "麻黄汤                  {'体证': ['头痛', '发热', '身疼', '腰痛', '骨节痛', '怕风', '...\n",
       "小柴胡汤                             {'体证': ['喜睡眠', '胸满胁痛'], '脉证': ['脉细']}\n",
       "大青龙汤                 {'体证': ['发热', '怕冷', '身体痛', '不出汗而烦躁'], '脉证': ['...\n",
       "小青龙汤                 {'体证': ['发热', '怕冷', '身体痛', '不出汗而烦躁'], '脉证': ['...\n",
       "桂枝加厚朴杏子汤                                 {'体证': ['微喘'], '脉证': ['脉浮紧']}\n",
       "干姜附子汤                {'体证': ['发热', '怕冷', '身体痛', '不出汗而烦躁'], '脉证': ['...\n",
       "桂枝加芍药生姜各一两人参三两新加汤    {'体证': ['发热', '怕冷', '身体痛', '不出汗而烦躁'], '脉证': ['...\n",
       "麻黄杏仁甘草石膏汤            {'体证': ['发热', '怕冷', '身体痛', '不出汗而烦躁'], '脉证': ['...\n",
       "桂枝甘草汤                    {'体证': ['心悸', '手心冒汗', '发汗过多'], '脉证': ['脉浮紧']}\n",
       "茯苓桂枝甘草大枣汤                       {'体证': ['肚脐下悸动', '发汗'], '脉证': ['脉浮紧']}\n",
       "茯苓桂枝白术甘草汤                   {'体证': ['起身头眩晕', '心口下气上冲'], '脉证': ['脉沉紧']}\n",
       "芍药甘草附子汤                               {'体证': ['发汗而怕冷'], '脉证': ['脉沉紧']}\n",
       "茯苓四逆汤                                 {'体证': ['发汗而怕冷'], '脉证': ['脉沉紧']}\n",
       "                                           ...                        \n",
       "麻黄连轺赤小豆汤                                 {'体证': ['消渴'], '脉证': ['脉沉紧']}\n",
       "桂枝加芍药汤               {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...\n",
       "桂枝加大黄汤               {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...\n",
       "麻黄细辛附子汤              {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...\n",
       "麻黄附子甘草汤              {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...\n",
       "黄连阿胶汤                {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...\n",
       "附子汤                  {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...\n",
       "桃花汤                  {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...\n",
       "猪肤汤                  {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...\n",
       "甘草汤                  {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...\n",
       "桔梗汤                  {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...\n",
       "苦酒汤                  {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...\n",
       "半夏散及汤                {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...\n",
       "白通汤                  {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...\n",
       "白通加猪胆汁汤              {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...\n",
       "通脉四逆汤                {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...\n",
       "四逆散                  {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...\n",
       "乌梅丸                  {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...\n",
       "当归四逆汤                {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...\n",
       "当归四逆加吴茱萸生姜汤          {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...\n",
       "麻黄升麻汤                                     {'体证': ['暂无'], '脉证': ['暂无']}\n",
       "干姜黄芩黄连人参汤                                 {'体证': ['暂无'], '脉证': ['暂无']}\n",
       "白头翁汤                 {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...\n",
       "四逆加人参汤                           {'体证': ['喜睡眠', '胸满胁痛'], '脉证': ['脉细']}\n",
       "理中丸                                      {'体证': ['消渴'], '脉证': ['脉沉紧']}\n",
       "通脉四逆加猪胆汤             {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...\n",
       "烧裈散                  {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...\n",
       "枳实栀子汤                {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...\n",
       "牡蛎泽泻散                            {'体证': ['喜睡眠', '胸满胁痛'], '脉证': ['脉细']}\n",
       "竹叶石膏汤                                    {'体证': ['消渴'], '脉证': ['脉沉紧']}\n",
       "Name: 证, Length: 111, dtype: object"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sh1.loc['证']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "zz = {'鼻涕','怕风'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = sh1.loc['证'].apply(lambda x: set(x['体证']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "桂枝汤\n"
     ]
    }
   ],
   "source": [
    "print(a[a.apply(lambda x: zz < x)].index[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = '怕风'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"'怕风'\""
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "repr(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "怕风\n"
     ]
    }
   ],
   "source": [
    "print(str(s))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'桂枝'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-30-6ba24e1e7e9a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msh1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'方'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'桂枝'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/anaconda3/lib/python3.7/site-packages/pandas/core/series.py\u001b[0m in \u001b[0;36mapply\u001b[0;34m(self, func, convert_dtype, args, **kwds)\u001b[0m\n\u001b[1;32m   3192\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3193\u001b[0m                 \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobject\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3194\u001b[0;31m                 \u001b[0mmapped\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmap_infer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconvert\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mconvert_dtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3195\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3196\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmapped\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmapped\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mSeries\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/src/inference.pyx\u001b[0m in \u001b[0;36mpandas._libs.lib.map_infer\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32m<ipython-input-30-6ba24e1e7e9a>\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m(x)\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msh1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'方'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'桂枝'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m: '桂枝'"
     ]
    }
   ],
   "source": [
    "len(sh1.loc['方'].apply(lambda x: x['桂枝']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "六经                              {'阴阳': '阴', '三经': '厥阴'}\n",
      "原文    {'对应证原文': ['吐利汗出。发热恶寒。四肢拘急。手足厥冷者。四逆汤主之。', '既吐且...\n",
      "方                 {'附子': '1枚', '炙甘草': '2两', '干姜': '1两'}\n",
      "证     {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...\n",
      "Name: 四逆汤, dtype: object\n"
     ]
    }
   ],
   "source": [
    "br1.find('四逆汤')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>中轴(土)</th>\n",
       "      <th>向下(金)</th>\n",
       "      <th>火</th>\n",
       "      <th>收藏(水)</th>\n",
       "      <th>向上(木)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>值</th>\n",
       "      <td>90</td>\n",
       "      <td>60</td>\n",
       "      <td>150</td>\n",
       "      <td>30</td>\n",
       "      <td>120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>味</th>\n",
       "      <td>甘甜</td>\n",
       "      <td>酸</td>\n",
       "      <td>咸</td>\n",
       "      <td>苦</td>\n",
       "      <td>辛辣</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>药物</th>\n",
       "      <td>[炙甘草, 人参, 大枣, 茯苓, 胶饴, 麦门冬, 升麻, 瓜蒂, 鸡子黄]</td>\n",
       "      <td>[芍药, 柴胡, 杏仁, 石膏, 五味子, 枳实, 铅丹, 龙骨, 牡蛎, 豉, 香豉]</td>\n",
       "      <td>[大黄, 芒硝, 黄连, 黄芩, 泽泻, 厚朴, 通草, 葱白]</td>\n",
       "      <td>[地黄, 麻黄, 葛根, 白术, 知母, 猪苓, 栀子, 香豉, 竹叶, 栀子]</td>\n",
       "      <td>[生姜, 附子, 桂枝, 半夏, 干姜, 粳米, 细辛, 阿胶, 赤小豆, 蜀椒]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      中轴(土)  \\\n",
       "值                                        90   \n",
       "味                                        甘甜   \n",
       "药物  [炙甘草, 人参, 大枣, 茯苓, 胶饴, 麦门冬, 升麻, 瓜蒂, 鸡子黄]   \n",
       "\n",
       "                                           向下(金)  \\\n",
       "值                                             60   \n",
       "味                                              酸   \n",
       "药物  [芍药, 柴胡, 杏仁, 石膏, 五味子, 枳实, 铅丹, 龙骨, 牡蛎, 豉, 香豉]   \n",
       "\n",
       "                                   火  \\\n",
       "值                                150   \n",
       "味                                  咸   \n",
       "药物  [大黄, 芒硝, 黄连, 黄芩, 泽泻, 厚朴, 通草, 葱白]   \n",
       "\n",
       "                                       收藏(水)  \\\n",
       "值                                         30   \n",
       "味                                          苦   \n",
       "药物  [地黄, 麻黄, 葛根, 白术, 知母, 猪苓, 栀子, 香豉, 竹叶, 栀子]   \n",
       "\n",
       "                                        向上(木)  \n",
       "值                                         120  \n",
       "味                                          辛辣  \n",
       "药物  [生姜, 附子, 桂枝, 半夏, 干姜, 粳米, 细辛, 阿胶, 赤小豆, 蜀椒]  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: 0, 1: 1, 2: 2, 3: 3, 4: 4, 5: 5, 6: 6, 7: 7, 8: 8, 9: 9}"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "{i: i for i in range(10)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'炙甘草': '中轴(土)',\n",
       " '人参': '中轴(土)',\n",
       " '大枣': '中轴(土)',\n",
       " '茯苓': '中轴(土)',\n",
       " '胶饴': '中轴(土)',\n",
       " '麦门冬': '中轴(土)',\n",
       " '升麻': '中轴(土)',\n",
       " '瓜蒂': '中轴(土)',\n",
       " '鸡子黄': '中轴(土)',\n",
       " '芍药': '向下(金)',\n",
       " '柴胡': '向下(金)',\n",
       " '杏仁': '向下(金)',\n",
       " '石膏': '向下(金)',\n",
       " '五味子': '向下(金)',\n",
       " '枳实': '向下(金)',\n",
       " '铅丹': '向下(金)',\n",
       " '龙骨': '向下(金)',\n",
       " '牡蛎': '向下(金)',\n",
       " '豉': '向下(金)',\n",
       " '香豉': '收藏(水)',\n",
       " '大黄': '火',\n",
       " '芒硝': '火',\n",
       " '黄连': '火',\n",
       " '黄芩': '火',\n",
       " '泽泻': '火',\n",
       " '厚朴': '火',\n",
       " '通草': '火',\n",
       " '葱白': '火',\n",
       " '地黄': '收藏(水)',\n",
       " '麻黄': '收藏(水)',\n",
       " '葛根': '收藏(水)',\n",
       " '白术': '收藏(水)',\n",
       " '知母': '收藏(水)',\n",
       " '猪苓': '收藏(水)',\n",
       " '栀子': '收藏(水)',\n",
       " '竹叶': '收藏(水)',\n",
       " '生姜': '向上(木)',\n",
       " '附子': '向上(木)',\n",
       " '桂枝': '向上(木)',\n",
       " '半夏': '向上(木)',\n",
       " '干姜': '向上(木)',\n",
       " '粳米': '向上(木)',\n",
       " '细辛': '向上(木)',\n",
       " '阿胶': '向上(木)',\n",
       " '赤小豆': '向上(木)',\n",
       " '蜀椒': '向上(木)'}"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "{y: sx for sx, yao in w.loc[\"药物\"].iteritems() for y in yao}  # 字典生成shi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'炙甘草': '中轴(土)',\n",
       " '人参': '中轴(土)',\n",
       " '大枣': '中轴(土)',\n",
       " '茯苓': '中轴(土)',\n",
       " '胶饴': '中轴(土)',\n",
       " '麦门冬': '中轴(土)',\n",
       " '升麻': '中轴(土)',\n",
       " '瓜蒂': '中轴(土)',\n",
       " '鸡子黄': '中轴(土)',\n",
       " '芍药': '向下(金)',\n",
       " '柴胡': '向下(金)',\n",
       " '杏仁': '向下(金)',\n",
       " '石膏': '向下(金)',\n",
       " '五味子': '向下(金)',\n",
       " '枳实': '向下(金)',\n",
       " '铅丹': '向下(金)',\n",
       " '龙骨': '向下(金)',\n",
       " '牡蛎': '向下(金)',\n",
       " '豉': '向下(金)',\n",
       " '香豉': '收藏(水)',\n",
       " '大黄': '火',\n",
       " '芒硝': '火',\n",
       " '黄连': '火',\n",
       " '黄芩': '火',\n",
       " '泽泻': '火',\n",
       " '厚朴': '火',\n",
       " '通草': '火',\n",
       " '葱白': '火',\n",
       " '地黄': '收藏(水)',\n",
       " '麻黄': '收藏(水)',\n",
       " '葛根': '收藏(水)',\n",
       " '白术': '收藏(水)',\n",
       " '知母': '收藏(水)',\n",
       " '猪苓': '收藏(水)',\n",
       " '栀子': '收藏(水)',\n",
       " '竹叶': '收藏(水)',\n",
       " '生姜': '向上(木)',\n",
       " '附子': '向上(木)',\n",
       " '桂枝': '向上(木)',\n",
       " '半夏': '向上(木)',\n",
       " '干姜': '向上(木)',\n",
       " '粳米': '向上(木)',\n",
       " '细辛': '向上(木)',\n",
       " '阿胶': '向上(木)',\n",
       " '赤小豆': '向上(木)',\n",
       " '蜀椒': '向上(木)'}"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_x = {}\n",
    "for sx, yao in w.loc[\"药物\"].iteritems():\n",
    "    for y in yao:\n",
    "        y_x[y] = sx\n",
    "y_x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>桂枝汤</th>\n",
       "      <th>桂枝加葛根汤</th>\n",
       "      <th>桂枝加附子汤</th>\n",
       "      <th>桂枝去芍药汤</th>\n",
       "      <th>桂枝去芍药加附子汤</th>\n",
       "      <th>桂枝麻黄各半汤</th>\n",
       "      <th>桂枝二麻黄一汤</th>\n",
       "      <th>白虎加人参汤</th>\n",
       "      <th>桂枝二越婢一汤</th>\n",
       "      <th>桂枝去桂加茯苓白术汤</th>\n",
       "      <th>...</th>\n",
       "      <th>麻黄升麻汤</th>\n",
       "      <th>干姜黄芩黄连人参汤</th>\n",
       "      <th>白头翁汤</th>\n",
       "      <th>四逆加人参汤</th>\n",
       "      <th>理中丸</th>\n",
       "      <th>通脉四逆加猪胆汤</th>\n",
       "      <th>烧裈散</th>\n",
       "      <th>枳实栀子汤</th>\n",
       "      <th>牡蛎泽泻散</th>\n",
       "      <th>竹叶石膏汤</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>六经</th>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '阳明'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>...</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '少阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '阳明'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '阳明'}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>原文</th>\n",
       "      <td>{'对应证原文': ['吐利止。而身痛不休者。当消息和解其外。宜桂枝汤小和之。'], '方剂...</td>\n",
       "      <td>{'对应证原文': ['太阳病，项背强几几，反汗出恶风者，桂枝加葛根汤主之。', '太阳与阳...</td>\n",
       "      <td>{'对应证原文': ['太阳病，发汗，遂漏不止，其人恶风，小便难，四支微急，难以屈伸者，桂枝...</td>\n",
       "      <td>{'对应证原文': ['太阳病。下之后。脉促。胸满者。桂枝去芍药汤主之。'], '方剂原文'...</td>\n",
       "      <td>{'对应证原文': ['若微寒者。桂枝去芍药加附子汤主之。'], '方剂原文': '桂枝三两...</td>\n",
       "      <td>{'对应证原文': ['面色反有热色者。未欲解也。以其不能得小汗出 。 身必痒。宜桂枝麻黄各...</td>\n",
       "      <td>{'对应证原文': ['服桂枝汤。大汗出。脉洪大者。与桂枝汤如前法。若形似疟。一日再发者。汗...</td>\n",
       "      <td>{'对应证原文': ['若渴欲饮水。口干舌燥者。白虎加人参汤主之。'], '方剂原文': '...</td>\n",
       "      <td>{'对应证原文': ['太阳病。发热恶寒。热多寒少。脉微弱者。此无阳也。不可发汗。宜桂枝二越...</td>\n",
       "      <td>{'对应证原文': ['服桂枝汤。或下之。仍头项强痛。翕翕发热。无汗。心下满微痛。小便不利者...</td>\n",
       "      <td>...</td>\n",
       "      <td>{'对应证原文': ['伤寒。六七日。大下后。寸脉沉而迟。手足厥逆。下部脉不至。喉咽不利。唾...</td>\n",
       "      <td>{'对应证原文': ['伤寒。本自寒下。医复吐下之。寒格。更逆吐下。若食入口即吐。干姜黄芩黄...</td>\n",
       "      <td>{'对应证原文': ['热利下重者。白头翁汤主之。'], '方剂原文': '白头翁二两 黄蘗...</td>\n",
       "      <td>{'对应证原文': ['恶寒。脉微而复利。利止。亡血也。四逆加人参汤主之。'], '方剂原文...</td>\n",
       "      <td>{'对应证原文': ['大病差后。喜唾。久不了了。胸上有寒。当以丸药温之。宜理中丸。'], ...</td>\n",
       "      <td>{'对应证原文': ['吐已下断。汗出而厥。四肢拘急不解。脉微欲绝者。通脉四逆加猪胆汤主之。...</td>\n",
       "      <td>{'对应证原文': ['伤寒阴易之为病。其人身体重。少气。少腹里急。或引阴中拘挛。热上冲胸。...</td>\n",
       "      <td>{'对应证原文': ['大病差后。劳复者。枳实栀子汤主之。'], '方剂原文': '枳实三枚...</td>\n",
       "      <td>{'对应证原文': ['大病差后。从腰以下有水气者。牡蛎泽泻散主之。'], '方剂原文': ...</td>\n",
       "      <td>{'对应证原文': ['伤寒解后。虚羸少气。气逆欲吐。竹叶石膏汤主之。'], '方剂原文':...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>方</th>\n",
       "      <td>{'桂枝': '3两', '芍药': '3两', '炙甘草': '2两', '生姜': '3...</td>\n",
       "      <td>{'葛根': '4两', '桂枝': '3两', '芍药': '2两', '炙甘草': '2...</td>\n",
       "      <td>{'附子': '1两', '桂枝': '3两', '芍药': '3两', '炙甘草': '3...</td>\n",
       "      <td>{'桂枝': '3两', '炙甘草': '2两', '生姜': '3两', '大枣': '1...</td>\n",
       "      <td>{'桂枝': '3两', '炙甘草': '2两', '生姜': '3两', '大枣': '1...</td>\n",
       "      <td>{'桂枝': '1两16铢', '炙甘草': '1两', '生姜': '1两', '大枣':...</td>\n",
       "      <td>{'桂枝': '1两17铢', '炙甘草': '1两6铢', '生姜': '1两6铢', '...</td>\n",
       "      <td>{'知母': '6两', '石膏': '1斤', '粳米': '6合', '炙甘草': '2...</td>\n",
       "      <td>{'桂枝': '1两', '芍药': '1两', '炙甘草': '1两', '麻黄': '1...</td>\n",
       "      <td>{'白术': '3两', '芍药': '3两', '炙甘草': '2两', '茯苓': '3...</td>\n",
       "      <td>...</td>\n",
       "      <td>{'茯苓': '6株', '炙甘草': '6株', '干姜': '6株', '桂枝': '6...</td>\n",
       "      <td>{'人参': '3两', '黄芩': '3两', '干姜': '3两', '黄连': '3两'}</td>\n",
       "      <td>{'白头翁': '2两', '黄蘗': '3两', '黄连': '3两', '秦皮': '3两'}</td>\n",
       "      <td>{'人参': '1两', '附子': '1枚', '炙甘草': '3两', '干姜': '1...</td>\n",
       "      <td>{'人参': '3两', '干姜': '3两', '炙甘草': '3两', '白术': '3两'}</td>\n",
       "      <td>{'附子': '1枚', '炙甘草': '2两', '干姜': '3两', '猪胆汁': '...</td>\n",
       "      <td>{'妇人中裈近隐处之烧灰': '一些'}</td>\n",
       "      <td>{'枳实': '3枚', '栀子': '14个', '豉': '1升'}</td>\n",
       "      <td>{'柴胡': '0.5斤', '黄芩': '3两', '人参': '3两', '半夏': '...</td>\n",
       "      <td>{'竹叶': '2把', '石膏': '1斤', '半夏': '1升', '麦门冬': '1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>证</th>\n",
       "      <td>{'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...</td>\n",
       "      <td>{'体证': ['肌肉酸痛', '怕风'], '脉证': ['无']}</td>\n",
       "      <td>{'体证': ['大量出汗不止', '怕风', '小便难', '四肢难以屈伸'], '脉证'...</td>\n",
       "      <td>{'体证': ['大便后胸胀'], '脉证': ['急促']}</td>\n",
       "      <td>{'体证': ['口苦', '轻微寒冷'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['身痒'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['暂无'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['暂无'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['发热怕冷', '热多寒少'], '脉证': ['微弱']}</td>\n",
       "      <td>{'体证': ['严重头痛', '发热无汗', '心下满', '小便不多', '身体微痛']...</td>\n",
       "      <td>...</td>\n",
       "      <td>{'体证': ['暂无'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['暂无'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...</td>\n",
       "      <td>{'体证': ['喜睡眠', '胸满胁痛'], '脉证': ['脉细']}</td>\n",
       "      <td>{'体证': ['消渴'], '脉证': ['脉沉紧']}</td>\n",
       "      <td>{'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...</td>\n",
       "      <td>{'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...</td>\n",
       "      <td>{'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...</td>\n",
       "      <td>{'体证': ['喜睡眠', '胸满胁痛'], '脉证': ['脉细']}</td>\n",
       "      <td>{'体证': ['消渴'], '脉证': ['脉沉紧']}</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4 rows × 111 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  桂枝汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['吐利止。而身痛不休者。当消息和解其外。宜桂枝汤小和之。'], '方剂...   \n",
       "方   {'桂枝': '3两', '芍药': '3两', '炙甘草': '2两', '生姜': '3...   \n",
       "证   {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...   \n",
       "\n",
       "                                               桂枝加葛根汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['太阳病，项背强几几，反汗出恶风者，桂枝加葛根汤主之。', '太阳与阳...   \n",
       "方   {'葛根': '4两', '桂枝': '3两', '芍药': '2两', '炙甘草': '2...   \n",
       "证                 {'体证': ['肌肉酸痛', '怕风'], '脉证': ['无']}   \n",
       "\n",
       "                                               桂枝加附子汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['太阳病，发汗，遂漏不止，其人恶风，小便难，四支微急，难以屈伸者，桂枝...   \n",
       "方   {'附子': '1两', '桂枝': '3两', '芍药': '3两', '炙甘草': '3...   \n",
       "证   {'体证': ['大量出汗不止', '怕风', '小便难', '四肢难以屈伸'], '脉证'...   \n",
       "\n",
       "                                               桂枝去芍药汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['太阳病。下之后。脉促。胸满者。桂枝去芍药汤主之。'], '方剂原文'...   \n",
       "方   {'桂枝': '3两', '炙甘草': '2两', '生姜': '3两', '大枣': '1...   \n",
       "证                     {'体证': ['大便后胸胀'], '脉证': ['急促']}   \n",
       "\n",
       "                                            桂枝去芍药加附子汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['若微寒者。桂枝去芍药加附子汤主之。'], '方剂原文': '桂枝三两...   \n",
       "方   {'桂枝': '3两', '炙甘草': '2两', '生姜': '3两', '大枣': '1...   \n",
       "证                {'体证': ['口苦', '轻微寒冷'], '脉证': ['暂无']}   \n",
       "\n",
       "                                              桂枝麻黄各半汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['面色反有热色者。未欲解也。以其不能得小汗出 。 身必痒。宜桂枝麻黄各...   \n",
       "方   {'桂枝': '1两16铢', '炙甘草': '1两', '生姜': '1两', '大枣':...   \n",
       "证                        {'体证': ['身痒'], '脉证': ['暂无']}   \n",
       "\n",
       "                                              桂枝二麻黄一汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['服桂枝汤。大汗出。脉洪大者。与桂枝汤如前法。若形似疟。一日再发者。汗...   \n",
       "方   {'桂枝': '1两17铢', '炙甘草': '1两6铢', '生姜': '1两6铢', '...   \n",
       "证                        {'体证': ['暂无'], '脉证': ['暂无']}   \n",
       "\n",
       "                                               白虎加人参汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '阳明'}   \n",
       "原文  {'对应证原文': ['若渴欲饮水。口干舌燥者。白虎加人参汤主之。'], '方剂原文': '...   \n",
       "方   {'知母': '6两', '石膏': '1斤', '粳米': '6合', '炙甘草': '2...   \n",
       "证                        {'体证': ['暂无'], '脉证': ['暂无']}   \n",
       "\n",
       "                                              桂枝二越婢一汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['太阳病。发热恶寒。热多寒少。脉微弱者。此无阳也。不可发汗。宜桂枝二越...   \n",
       "方   {'桂枝': '1两', '芍药': '1两', '炙甘草': '1两', '麻黄': '1...   \n",
       "证              {'体证': ['发热怕冷', '热多寒少'], '脉证': ['微弱']}   \n",
       "\n",
       "                                           桂枝去桂加茯苓白术汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['服桂枝汤。或下之。仍头项强痛。翕翕发热。无汗。心下满微痛。小便不利者...   \n",
       "方   {'白术': '3两', '芍药': '3两', '炙甘草': '2两', '茯苓': '3...   \n",
       "证   {'体证': ['严重头痛', '发热无汗', '心下满', '小便不多', '身体微痛']...   \n",
       "\n",
       "                          ...                          \\\n",
       "六经                        ...                           \n",
       "原文                        ...                           \n",
       "方                         ...                           \n",
       "证                         ...                           \n",
       "\n",
       "                                                麻黄升麻汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['伤寒。六七日。大下后。寸脉沉而迟。手足厥逆。下部脉不至。喉咽不利。唾...   \n",
       "方   {'茯苓': '6株', '炙甘草': '6株', '干姜': '6株', '桂枝': '6...   \n",
       "证                        {'体证': ['暂无'], '脉证': ['暂无']}   \n",
       "\n",
       "                                            干姜黄芩黄连人参汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['伤寒。本自寒下。医复吐下之。寒格。更逆吐下。若食入口即吐。干姜黄芩黄...   \n",
       "方    {'人参': '3两', '黄芩': '3两', '干姜': '3两', '黄连': '3两'}   \n",
       "证                        {'体证': ['暂无'], '脉证': ['暂无']}   \n",
       "\n",
       "                                                 白头翁汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '少阴'}   \n",
       "原文  {'对应证原文': ['热利下重者。白头翁汤主之。'], '方剂原文': '白头翁二两 黄蘗...   \n",
       "方   {'白头翁': '2两', '黄蘗': '3两', '黄连': '3两', '秦皮': '3两'}   \n",
       "证   {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...   \n",
       "\n",
       "                                               四逆加人参汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['恶寒。脉微而复利。利止。亡血也。四逆加人参汤主之。'], '方剂原文...   \n",
       "方   {'人参': '1两', '附子': '1枚', '炙甘草': '3两', '干姜': '1...   \n",
       "证               {'体证': ['喜睡眠', '胸满胁痛'], '脉证': ['脉细']}   \n",
       "\n",
       "                                                  理中丸  \\\n",
       "六经                            {'阴阳': '阳', '三经': '阳明'}   \n",
       "原文  {'对应证原文': ['大病差后。喜唾。久不了了。胸上有寒。当以丸药温之。宜理中丸。'], ...   \n",
       "方   {'人参': '3两', '干姜': '3两', '炙甘草': '3两', '白术': '3两'}   \n",
       "证                       {'体证': ['消渴'], '脉证': ['脉沉紧']}   \n",
       "\n",
       "                                             通脉四逆加猪胆汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['吐已下断。汗出而厥。四肢拘急不解。脉微欲绝者。通脉四逆加猪胆汤主之。...   \n",
       "方   {'附子': '1枚', '炙甘草': '2两', '干姜': '3两', '猪胆汁': '...   \n",
       "证   {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...   \n",
       "\n",
       "                                                  烧裈散  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['伤寒阴易之为病。其人身体重。少气。少腹里急。或引阴中拘挛。热上冲胸。...   \n",
       "方                                {'妇人中裈近隐处之烧灰': '一些'}   \n",
       "证   {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...   \n",
       "\n",
       "                                                枳实栀子汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['大病差后。劳复者。枳实栀子汤主之。'], '方剂原文': '枳实三枚...   \n",
       "方                {'枳实': '3枚', '栀子': '14个', '豉': '1升'}   \n",
       "证   {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...   \n",
       "\n",
       "                                                牡蛎泽泻散  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['大病差后。从腰以下有水气者。牡蛎泽泻散主之。'], '方剂原文': ...   \n",
       "方   {'柴胡': '0.5斤', '黄芩': '3两', '人参': '3两', '半夏': '...   \n",
       "证               {'体证': ['喜睡眠', '胸满胁痛'], '脉证': ['脉细']}   \n",
       "\n",
       "                                                竹叶石膏汤  \n",
       "六经                            {'阴阳': '阳', '三经': '阳明'}  \n",
       "原文  {'对应证原文': ['伤寒解后。虚羸少气。气逆欲吐。竹叶石膏汤主之。'], '方剂原文':...  \n",
       "方   {'竹叶': '2把', '石膏': '1斤', '半夏': '1升', '麦门冬': '1...  \n",
       "证                       {'体证': ['消渴'], '脉证': ['脉沉紧']}  \n",
       "\n",
       "[4 rows x 111 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sh1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "桂枝汤                  {'桂枝': '3两', '芍药': '3两', '炙甘草': '2两', '生姜': '3...\n",
       "桂枝加葛根汤               {'葛根': '4两', '桂枝': '3两', '芍药': '2两', '炙甘草': '2...\n",
       "桂枝加附子汤               {'附子': '1两', '桂枝': '3两', '芍药': '3两', '炙甘草': '3...\n",
       "桂枝去芍药汤               {'桂枝': '3两', '炙甘草': '2两', '生姜': '3两', '大枣': '1...\n",
       "桂枝去芍药加附子汤            {'桂枝': '3两', '炙甘草': '2两', '生姜': '3两', '大枣': '1...\n",
       "桂枝麻黄各半汤              {'桂枝': '1两16铢', '炙甘草': '1两', '生姜': '1两', '大枣':...\n",
       "桂枝二麻黄一汤              {'桂枝': '1两17铢', '炙甘草': '1两6铢', '生姜': '1两6铢', '...\n",
       "白虎加人参汤               {'知母': '6两', '石膏': '1斤', '粳米': '6合', '炙甘草': '2...\n",
       "桂枝二越婢一汤              {'桂枝': '1两', '芍药': '1两', '炙甘草': '1两', '麻黄': '1...\n",
       "桂枝去桂加茯苓白术汤           {'白术': '3两', '芍药': '3两', '炙甘草': '2两', '茯苓': '3...\n",
       "甘草干姜汤                                        {'炙甘草': '4两', '干姜': '2两'}\n",
       "芍药甘草汤                                        {'芍药': '4两', '炙甘草': '4两'}\n",
       "调胃承气汤                          {'芒硝': '0.5升', '炙甘草': '2两', '大黄': '4两'}\n",
       "四逆汤                              {'附子': '1枚', '炙甘草': '2两', '干姜': '1两'}\n",
       "葛根汤                  {'葛根': '4两', '麻黄': '3两', '桂枝': '2两', '炙甘草': '2...\n",
       "葛根加半夏汤               {'葛根': '4两', '麻黄': '3两', '桂枝': '2两', '炙甘草': '2...\n",
       "葛根黄芩黄连汤              {'葛根': '0.5斤', '黄连': '3两', '黄芩': '3两', '炙甘草': ...\n",
       "麻黄汤                  {'麻黄': '3两', '桂枝': '2两', '杏仁': '70个', '炙甘草': '...\n",
       "小柴胡汤                 {'柴胡': '0.5斤', '黄芩': '3两', '人参': '3两', '半夏': '...\n",
       "大青龙汤                 {'麻黄': '6两', '桂枝': '2两', '大枣': '12枚', '石膏': '4...\n",
       "小青龙汤                 {'麻黄': '3两', '桂枝': '2两', '五味子': '0.5升', '半夏': ...\n",
       "桂枝加厚朴杏子汤             {'麻黄': '3两', '桂枝': '3两', '厚朴': '2两', '杏仁': '50...\n",
       "干姜附子汤                                         {'干姜': '1两', '附子': '1枚'}\n",
       "桂枝加芍药生姜各一两人参三两新加汤    {'桂枝': '3两', '芍药': '4两', '炙甘草': '2两', '人参': '3...\n",
       "麻黄杏仁甘草石膏汤            {'麻黄': '4两', '杏仁': '50个', '甘草': '2两', '石膏': '0...\n",
       "桂枝甘草汤                                        {'桂枝': '4两', '炙甘草': '2两'}\n",
       "茯苓桂枝甘草大枣汤            {'桂枝': '4两', '炙甘草': '2两', '茯苓': '0.5斤', '大枣': ...\n",
       "茯苓桂枝白术甘草汤            {'桂枝': '3两', '炙甘草': '2两', '茯苓': '4两', '白术': '2两'}\n",
       "芍药甘草附子汤                          {'芍药': '3两', '炙甘草': '3两', '附子': '1枚'}\n",
       "茯苓四逆汤                {'茯苓': '4两', '炙甘草': '3两', '附子': '1枚', '人参': '1...\n",
       "                                           ...                        \n",
       "麻黄连轺赤小豆汤             {'麻黄': '2两', '连轺': '2两', '杏仁': '40个', '赤小豆': '...\n",
       "桂枝加芍药汤               {'桂枝': '3两', '芍药': '3两', '炙甘草': '2两', '生姜': '3...\n",
       "桂枝加大黄汤               {'桂枝': '3两', '芍药': '6两', '炙甘草': '2两', '生姜': '3...\n",
       "麻黄细辛附子汤                           {'麻黄': '2两', '细辛': '2两', '附子': '1枚'}\n",
       "麻黄附子甘草汤                           {'麻黄': '2两', '甘草': '2两', '附子': '1枚'}\n",
       "黄连阿胶汤                {'黄连': '2两', '黄芩': '2两', '芍药': '1枚', '鸡子黄': '2...\n",
       "附子汤                  {'附子': '2枚', '茯苓': '3两', '人参': '2两', '白术': '4两...\n",
       "桃花汤                  {'附子': '2枚', '茯苓': '3两', '人参': '2两', '白术': '4两...\n",
       "猪肤汤                                                       {'猪肤': '1斤'}\n",
       "甘草汤                                                       {'甘草': '2两'}\n",
       "桔梗汤                                           {'甘草': '2两', '桔梗': '1两'}\n",
       "苦酒汤                                          {'半夏': '14枚', '鸡子': '1枚'}\n",
       "半夏散及汤                            {'半夏': '未写', '桂枝': '未写', '炙甘草': '未写'}\n",
       "白通汤                               {'葱白': '4茎', '干姜': '1两', '附子': '1枚'}\n",
       "白通加猪胆汁汤              {'葱白': '4茎', '干姜': '1两', '附子': '1枚', '人尿': '5合...\n",
       "通脉四逆汤                            {'附子': '1枚', '炙甘草': '2两', '干姜': '3两'}\n",
       "四逆散                  {'柴胡': '未写', '炙甘草': '未写', '枳实': '未写', '芍药': '未写'}\n",
       "乌梅丸                  {'附子': '6两', '炙甘草': '2两', '干姜': '10两', '乌梅': '...\n",
       "当归四逆汤                {'当归': '3两', '炙甘草': '2两', '桂枝': '3两', '芍药': '3...\n",
       "当归四逆加吴茱萸生姜汤          {'当归': '3两', '炙甘草': '2两', '桂枝': '3两', '芍药': '3...\n",
       "麻黄升麻汤                {'茯苓': '6株', '炙甘草': '6株', '干姜': '6株', '桂枝': '6...\n",
       "干姜黄芩黄连人参汤             {'人参': '3两', '黄芩': '3两', '干姜': '3两', '黄连': '3两'}\n",
       "白头翁汤                 {'白头翁': '2两', '黄蘗': '3两', '黄连': '3两', '秦皮': '3两'}\n",
       "四逆加人参汤               {'人参': '1两', '附子': '1枚', '炙甘草': '3两', '干姜': '1...\n",
       "理中丸                  {'人参': '3两', '干姜': '3两', '炙甘草': '3两', '白术': '3两'}\n",
       "通脉四逆加猪胆汤             {'附子': '1枚', '炙甘草': '2两', '干姜': '3两', '猪胆汁': '...\n",
       "烧裈散                                               {'妇人中裈近隐处之烧灰': '一些'}\n",
       "枳实栀子汤                             {'枳实': '3枚', '栀子': '14个', '豉': '1升'}\n",
       "牡蛎泽泻散                {'柴胡': '0.5斤', '黄芩': '3两', '人参': '3两', '半夏': '...\n",
       "竹叶石膏汤                {'竹叶': '2把', '石膏': '1斤', '半夏': '1升', '麦门冬': '1...\n",
       "Name: 方, Length: 111, dtype: object"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fang = sh1.loc[\"方\"]\n",
    "fang"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'向上(木)': 0.2824427480916031,\n",
       " '向下(金)': 0.13740458015267176,\n",
       " '中轴(土)': 0.26717557251908397,\n",
       " '收藏(水)': 0.08969465648854962,\n",
       " '火': 0.11068702290076336,\n",
       " '土': 0.11259541984732824}"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sx = [y_x.get(y, \"土\") for f in fang for y in f]\n",
    "sx_len = len(sx)\n",
    "{y: cnt / sx_len for y, cnt in collections.Counter(sx).items()}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'x' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-39-06f92b990b8b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     14\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     15\u001b[0m \u001b[0mfig\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 16\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpie\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mautopct\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'%1.2f%%'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m#画饼图（数据，数据对应的标签，百分数保留两位小数点）\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     17\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtitle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Pie chart\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     18\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'x' is not defined"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import collections\n",
    "\n",
    "def count(x):\n",
    "    sx = [y_x.get(y, \"土\") for y in x]\n",
    "    x_len = len(x)\n",
    "#     d = {}\n",
    "#     print(sx)\n",
    "#     for s, cnt in collections.Counter(sx).items():\n",
    "#         d[s] = cnt / x_len\n",
    "#     return d\n",
    "    return {s: cnt / x_len for s, cnt in collections.Counter(sx).items()}#字典解析\n",
    "\n",
    "q1 = fang.apply(count)\n",
    "\n",
    "fig = plt.figure()\n",
    "plt.pie(x,labels=labels,autopct='%1.2f%%') #画饼图（数据，数据对应的标签，百分数保留两位小数点）\n",
    "plt.title(\"Pie chart\")\n",
    "  \n",
    " \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "import collections"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_items([(1, 2), (3, 1)])"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "collections.Counter([1, 1, 3]).items()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>桂枝汤</th>\n",
       "      <th>桂枝加葛根汤</th>\n",
       "      <th>桂枝加附子汤</th>\n",
       "      <th>桂枝去芍药汤</th>\n",
       "      <th>桂枝去芍药加附子汤</th>\n",
       "      <th>桂枝麻黄各半汤</th>\n",
       "      <th>桂枝二麻黄一汤</th>\n",
       "      <th>白虎加人参汤</th>\n",
       "      <th>桂枝二越婢一汤</th>\n",
       "      <th>桂枝去桂加茯苓白术汤</th>\n",
       "      <th>...</th>\n",
       "      <th>麻黄升麻汤</th>\n",
       "      <th>干姜黄芩黄连人参汤</th>\n",
       "      <th>白头翁汤</th>\n",
       "      <th>四逆加人参汤</th>\n",
       "      <th>理中丸</th>\n",
       "      <th>通脉四逆加猪胆汤</th>\n",
       "      <th>烧裈散</th>\n",
       "      <th>枳实栀子汤</th>\n",
       "      <th>牡蛎泽泻散</th>\n",
       "      <th>竹叶石膏汤</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>六经</th>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '阳明'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '太阳'}</td>\n",
       "      <td>...</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '少阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '阳明'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阴', '三经': '厥阴'}</td>\n",
       "      <td>{'阴阳': '阳', '三经': '阳明'}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>原文</th>\n",
       "      <td>{'对应证原文': ['吐利止。而身痛不休者。当消息和解其外。宜桂枝汤小和之。'], '方剂...</td>\n",
       "      <td>{'对应证原文': ['太阳病，项背强几几，反汗出恶风者，桂枝加葛根汤主之。', '太阳与阳...</td>\n",
       "      <td>{'对应证原文': ['太阳病，发汗，遂漏不止，其人恶风，小便难，四支微急，难以屈伸者，桂枝...</td>\n",
       "      <td>{'对应证原文': ['太阳病。下之后。脉促。胸满者。桂枝去芍药汤主之。'], '方剂原文'...</td>\n",
       "      <td>{'对应证原文': ['若微寒者。桂枝去芍药加附子汤主之。'], '方剂原文': '桂枝三两...</td>\n",
       "      <td>{'对应证原文': ['面色反有热色者。未欲解也。以其不能得小汗出 。 身必痒。宜桂枝麻黄各...</td>\n",
       "      <td>{'对应证原文': ['服桂枝汤。大汗出。脉洪大者。与桂枝汤如前法。若形似疟。一日再发者。汗...</td>\n",
       "      <td>{'对应证原文': ['若渴欲饮水。口干舌燥者。白虎加人参汤主之。'], '方剂原文': '...</td>\n",
       "      <td>{'对应证原文': ['太阳病。发热恶寒。热多寒少。脉微弱者。此无阳也。不可发汗。宜桂枝二越...</td>\n",
       "      <td>{'对应证原文': ['服桂枝汤。或下之。仍头项强痛。翕翕发热。无汗。心下满微痛。小便不利者...</td>\n",
       "      <td>...</td>\n",
       "      <td>{'对应证原文': ['伤寒。六七日。大下后。寸脉沉而迟。手足厥逆。下部脉不至。喉咽不利。唾...</td>\n",
       "      <td>{'对应证原文': ['伤寒。本自寒下。医复吐下之。寒格。更逆吐下。若食入口即吐。干姜黄芩黄...</td>\n",
       "      <td>{'对应证原文': ['热利下重者。白头翁汤主之。'], '方剂原文': '白头翁二两 黄蘗...</td>\n",
       "      <td>{'对应证原文': ['恶寒。脉微而复利。利止。亡血也。四逆加人参汤主之。'], '方剂原文...</td>\n",
       "      <td>{'对应证原文': ['大病差后。喜唾。久不了了。胸上有寒。当以丸药温之。宜理中丸。'], ...</td>\n",
       "      <td>{'对应证原文': ['吐已下断。汗出而厥。四肢拘急不解。脉微欲绝者。通脉四逆加猪胆汤主之。...</td>\n",
       "      <td>{'对应证原文': ['伤寒阴易之为病。其人身体重。少气。少腹里急。或引阴中拘挛。热上冲胸。...</td>\n",
       "      <td>{'对应证原文': ['大病差后。劳复者。枳实栀子汤主之。'], '方剂原文': '枳实三枚...</td>\n",
       "      <td>{'对应证原文': ['大病差后。从腰以下有水气者。牡蛎泽泻散主之。'], '方剂原文': ...</td>\n",
       "      <td>{'对应证原文': ['伤寒解后。虚羸少气。气逆欲吐。竹叶石膏汤主之。'], '方剂原文':...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>方</th>\n",
       "      <td>{'桂枝': '3两', '芍药': '3两', '炙甘草': '2两', '生姜': '3...</td>\n",
       "      <td>{'葛根': '4两', '桂枝': '3两', '芍药': '2两', '炙甘草': '2...</td>\n",
       "      <td>{'附子': '1两', '桂枝': '3两', '芍药': '3两', '炙甘草': '3...</td>\n",
       "      <td>{'桂枝': '3两', '炙甘草': '2两', '生姜': '3两', '大枣': '1...</td>\n",
       "      <td>{'桂枝': '3两', '炙甘草': '2两', '生姜': '3两', '大枣': '1...</td>\n",
       "      <td>{'桂枝': '1两16铢', '炙甘草': '1两', '生姜': '1两', '大枣':...</td>\n",
       "      <td>{'桂枝': '1两17铢', '炙甘草': '1两6铢', '生姜': '1两6铢', '...</td>\n",
       "      <td>{'知母': '6两', '石膏': '1斤', '粳米': '6合', '炙甘草': '2...</td>\n",
       "      <td>{'桂枝': '1两', '芍药': '1两', '炙甘草': '1两', '麻黄': '1...</td>\n",
       "      <td>{'白术': '3两', '芍药': '3两', '炙甘草': '2两', '茯苓': '3...</td>\n",
       "      <td>...</td>\n",
       "      <td>{'茯苓': '6株', '炙甘草': '6株', '干姜': '6株', '桂枝': '6...</td>\n",
       "      <td>{'人参': '3两', '黄芩': '3两', '干姜': '3两', '黄连': '3两'}</td>\n",
       "      <td>{'白头翁': '2两', '黄蘗': '3两', '黄连': '3两', '秦皮': '3两'}</td>\n",
       "      <td>{'人参': '1两', '附子': '1枚', '炙甘草': '3两', '干姜': '1...</td>\n",
       "      <td>{'人参': '3两', '干姜': '3两', '炙甘草': '3两', '白术': '3两'}</td>\n",
       "      <td>{'附子': '1枚', '炙甘草': '2两', '干姜': '3两', '猪胆汁': '...</td>\n",
       "      <td>{'妇人中裈近隐处之烧灰': '一些'}</td>\n",
       "      <td>{'枳实': '3枚', '栀子': '14个', '豉': '1升'}</td>\n",
       "      <td>{'柴胡': '0.5斤', '黄芩': '3两', '人参': '3两', '半夏': '...</td>\n",
       "      <td>{'竹叶': '2把', '石膏': '1斤', '半夏': '1升', '麦门冬': '1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>证</th>\n",
       "      <td>{'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...</td>\n",
       "      <td>{'体证': ['肌肉酸痛', '怕风'], '脉证': ['无']}</td>\n",
       "      <td>{'体证': ['大量出汗不止', '怕风', '小便难', '四肢难以屈伸'], '脉证'...</td>\n",
       "      <td>{'体证': ['大便后胸胀'], '脉证': ['急促']}</td>\n",
       "      <td>{'体证': ['口苦', '轻微寒冷'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['身痒'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['暂无'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['暂无'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['发热怕冷', '热多寒少'], '脉证': ['微弱']}</td>\n",
       "      <td>{'体证': ['严重头痛', '发热无汗', '心下满', '小便不多', '身体微痛']...</td>\n",
       "      <td>...</td>\n",
       "      <td>{'体证': ['暂无'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['暂无'], '脉证': ['暂无']}</td>\n",
       "      <td>{'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...</td>\n",
       "      <td>{'体证': ['喜睡眠', '胸满胁痛'], '脉证': ['脉细']}</td>\n",
       "      <td>{'体证': ['消渴'], '脉证': ['脉沉紧']}</td>\n",
       "      <td>{'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...</td>\n",
       "      <td>{'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...</td>\n",
       "      <td>{'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...</td>\n",
       "      <td>{'体证': ['喜睡眠', '胸满胁痛'], '脉证': ['脉细']}</td>\n",
       "      <td>{'体证': ['消渴'], '脉证': ['脉沉紧']}</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4 rows × 111 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  桂枝汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['吐利止。而身痛不休者。当消息和解其外。宜桂枝汤小和之。'], '方剂...   \n",
       "方   {'桂枝': '3两', '芍药': '3两', '炙甘草': '2两', '生姜': '3...   \n",
       "证   {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...   \n",
       "\n",
       "                                               桂枝加葛根汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['太阳病，项背强几几，反汗出恶风者，桂枝加葛根汤主之。', '太阳与阳...   \n",
       "方   {'葛根': '4两', '桂枝': '3两', '芍药': '2两', '炙甘草': '2...   \n",
       "证                 {'体证': ['肌肉酸痛', '怕风'], '脉证': ['无']}   \n",
       "\n",
       "                                               桂枝加附子汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['太阳病，发汗，遂漏不止，其人恶风，小便难，四支微急，难以屈伸者，桂枝...   \n",
       "方   {'附子': '1两', '桂枝': '3两', '芍药': '3两', '炙甘草': '3...   \n",
       "证   {'体证': ['大量出汗不止', '怕风', '小便难', '四肢难以屈伸'], '脉证'...   \n",
       "\n",
       "                                               桂枝去芍药汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['太阳病。下之后。脉促。胸满者。桂枝去芍药汤主之。'], '方剂原文'...   \n",
       "方   {'桂枝': '3两', '炙甘草': '2两', '生姜': '3两', '大枣': '1...   \n",
       "证                     {'体证': ['大便后胸胀'], '脉证': ['急促']}   \n",
       "\n",
       "                                            桂枝去芍药加附子汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['若微寒者。桂枝去芍药加附子汤主之。'], '方剂原文': '桂枝三两...   \n",
       "方   {'桂枝': '3两', '炙甘草': '2两', '生姜': '3两', '大枣': '1...   \n",
       "证                {'体证': ['口苦', '轻微寒冷'], '脉证': ['暂无']}   \n",
       "\n",
       "                                              桂枝麻黄各半汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['面色反有热色者。未欲解也。以其不能得小汗出 。 身必痒。宜桂枝麻黄各...   \n",
       "方   {'桂枝': '1两16铢', '炙甘草': '1两', '生姜': '1两', '大枣':...   \n",
       "证                        {'体证': ['身痒'], '脉证': ['暂无']}   \n",
       "\n",
       "                                              桂枝二麻黄一汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['服桂枝汤。大汗出。脉洪大者。与桂枝汤如前法。若形似疟。一日再发者。汗...   \n",
       "方   {'桂枝': '1两17铢', '炙甘草': '1两6铢', '生姜': '1两6铢', '...   \n",
       "证                        {'体证': ['暂无'], '脉证': ['暂无']}   \n",
       "\n",
       "                                               白虎加人参汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '阳明'}   \n",
       "原文  {'对应证原文': ['若渴欲饮水。口干舌燥者。白虎加人参汤主之。'], '方剂原文': '...   \n",
       "方   {'知母': '6两', '石膏': '1斤', '粳米': '6合', '炙甘草': '2...   \n",
       "证                        {'体证': ['暂无'], '脉证': ['暂无']}   \n",
       "\n",
       "                                              桂枝二越婢一汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['太阳病。发热恶寒。热多寒少。脉微弱者。此无阳也。不可发汗。宜桂枝二越...   \n",
       "方   {'桂枝': '1两', '芍药': '1两', '炙甘草': '1两', '麻黄': '1...   \n",
       "证              {'体证': ['发热怕冷', '热多寒少'], '脉证': ['微弱']}   \n",
       "\n",
       "                                           桂枝去桂加茯苓白术汤  \\\n",
       "六经                            {'阴阳': '阳', '三经': '太阳'}   \n",
       "原文  {'对应证原文': ['服桂枝汤。或下之。仍头项强痛。翕翕发热。无汗。心下满微痛。小便不利者...   \n",
       "方   {'白术': '3两', '芍药': '3两', '炙甘草': '2两', '茯苓': '3...   \n",
       "证   {'体证': ['严重头痛', '发热无汗', '心下满', '小便不多', '身体微痛']...   \n",
       "\n",
       "                          ...                          \\\n",
       "六经                        ...                           \n",
       "原文                        ...                           \n",
       "方                         ...                           \n",
       "证                         ...                           \n",
       "\n",
       "                                                麻黄升麻汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['伤寒。六七日。大下后。寸脉沉而迟。手足厥逆。下部脉不至。喉咽不利。唾...   \n",
       "方   {'茯苓': '6株', '炙甘草': '6株', '干姜': '6株', '桂枝': '6...   \n",
       "证                        {'体证': ['暂无'], '脉证': ['暂无']}   \n",
       "\n",
       "                                            干姜黄芩黄连人参汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['伤寒。本自寒下。医复吐下之。寒格。更逆吐下。若食入口即吐。干姜黄芩黄...   \n",
       "方    {'人参': '3两', '黄芩': '3两', '干姜': '3两', '黄连': '3两'}   \n",
       "证                        {'体证': ['暂无'], '脉证': ['暂无']}   \n",
       "\n",
       "                                                 白头翁汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '少阴'}   \n",
       "原文  {'对应证原文': ['热利下重者。白头翁汤主之。'], '方剂原文': '白头翁二两 黄蘗...   \n",
       "方   {'白头翁': '2两', '黄蘗': '3两', '黄连': '3两', '秦皮': '3两'}   \n",
       "证   {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...   \n",
       "\n",
       "                                               四逆加人参汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['恶寒。脉微而复利。利止。亡血也。四逆加人参汤主之。'], '方剂原文...   \n",
       "方   {'人参': '1两', '附子': '1枚', '炙甘草': '3两', '干姜': '1...   \n",
       "证               {'体证': ['喜睡眠', '胸满胁痛'], '脉证': ['脉细']}   \n",
       "\n",
       "                                                  理中丸  \\\n",
       "六经                            {'阴阳': '阳', '三经': '阳明'}   \n",
       "原文  {'对应证原文': ['大病差后。喜唾。久不了了。胸上有寒。当以丸药温之。宜理中丸。'], ...   \n",
       "方   {'人参': '3两', '干姜': '3两', '炙甘草': '3两', '白术': '3两'}   \n",
       "证                       {'体证': ['消渴'], '脉证': ['脉沉紧']}   \n",
       "\n",
       "                                             通脉四逆加猪胆汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['吐已下断。汗出而厥。四肢拘急不解。脉微欲绝者。通脉四逆加猪胆汤主之。...   \n",
       "方   {'附子': '1枚', '炙甘草': '2两', '干姜': '3两', '猪胆汁': '...   \n",
       "证   {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...   \n",
       "\n",
       "                                                  烧裈散  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['伤寒阴易之为病。其人身体重。少气。少腹里急。或引阴中拘挛。热上冲胸。...   \n",
       "方                                {'妇人中裈近隐处之烧灰': '一些'}   \n",
       "证   {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...   \n",
       "\n",
       "                                                枳实栀子汤  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['大病差后。劳复者。枳实栀子汤主之。'], '方剂原文': '枳实三枚...   \n",
       "方                {'枳实': '3枚', '栀子': '14个', '豉': '1升'}   \n",
       "证   {'体证': ['四肢冷', '长期焦虑', '自感体虚', '长期抑郁', '没有精神',...   \n",
       "\n",
       "                                                牡蛎泽泻散  \\\n",
       "六经                            {'阴阳': '阴', '三经': '厥阴'}   \n",
       "原文  {'对应证原文': ['大病差后。从腰以下有水气者。牡蛎泽泻散主之。'], '方剂原文': ...   \n",
       "方   {'柴胡': '0.5斤', '黄芩': '3两', '人参': '3两', '半夏': '...   \n",
       "证               {'体证': ['喜睡眠', '胸满胁痛'], '脉证': ['脉细']}   \n",
       "\n",
       "                                                竹叶石膏汤  \n",
       "六经                            {'阴阳': '阳', '三经': '阳明'}  \n",
       "原文  {'对应证原文': ['伤寒解后。虚羸少气。气逆欲吐。竹叶石膏汤主之。'], '方剂原文':...  \n",
       "方   {'竹叶': '2把', '石膏': '1斤', '半夏': '1升', '麦门冬': '1...  \n",
       "证                       {'体证': ['消渴'], '脉证': ['脉沉紧']}  \n",
       "\n",
       "[4 rows x 111 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sh1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4, 111)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sh1.shape#貌似没算重复,这个不行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "六经                              {'阴阳': '阴', '三经': '厥阴'}\n",
       "原文    {'对应证原文': ['吐利止。而身痛不休者。当消息和解其外。宜桂枝汤小和之。'], '方剂...\n",
       "方     {'桂枝': '3两', '芍药': '3两', '炙甘草': '2两', '生姜': '3...\n",
       "证     {'体证': ['发热', '鼻涕', '怕冷', '怕风', '干呕', '头痛', '出...\n",
       "Name: 桂枝汤, dtype: object"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sh1.桂枝汤"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "file_extension": ".py",
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